[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-machine-learning-us":3,"job-search-\u002Fen-us\u002Fjobs-by-skill\u002Fmachine-learning":33,"skill-page-filters-\u002Fen-us\u002Fjobs-by-skill\u002Fmachine-learning":822,"featured-jobs-\u002Fen-us\u002Fjobs-by-skill\u002Fmachine-learning":1002},{"image_path":4,"content_de":5,"content_en":18,"composite_key":31,"last_updated":32},"\u002Fimages\u002Fskill\u002Fmachine-learning.webp",{"tab1":6,"tab2":9,"tab3":12,"tab4":15},{"title":7,"content":8},"Bedeutung & Relevanz","**Maschinelles Lernen** (Machine Learning) hat in den **Vereinigten Staaten** eine enorme strategische Bedeutung erlangt, insbesondere in der Finanz- und Versicherungsbranche. Diese Technologie revolutioniert traditionelle Prozesse durch datengesteuerte Entscheidungsfindung und automatisierte Analysen. In der **Versicherungsbranche** ([Insurance](\u002Fjobs-by-industry\u002Finsurance)) ermöglicht maschinelles Lernen präzisere Risikobewertungen, Betrugserkennung in Echtzeit und personalisierte Policen. Bei **Investment Management** ([Investment Management](\u002Fjobs-by-industry\u002Finvestment-management)) optimiert es Portfoliostrategien, identifiziert Markttrends und verbessert die Anlageperformance durch prädiktive Analysen.\n\nFührende Unternehmen wie **Allianz Insurance** und **Pacific Investment Mgt Co. LLC** setzen maschinelles Lernen ein, um Wettbewerbsvorteile zu sichern und operative Effizienz zu steigern. Die Technologie unterstützt komplexe Aufgaben wie **Risikomodellierung** ([Risk Modeling](\u002Fjobs-by-expertise\u002Frisk-modeling)), **Schadenmodellierung** ([Loss Modeling](\u002Fjobs-by-expertise\u002Floss-modeling)) und **Katastrophenanalyse** ([Catastrophe Analysis](\u002Fjobs-by-expertise\u002Fcatastrophe-analysis)), was in volatilen Märkten entscheidend ist. Mit der zunehmenden Datenmenge und Rechenleistung wird maschinelles Lernen weiterhin Wachstum und Innovation in den **Vereinigten Staaten** antreiben.",{"title":10,"content":11},"Top-Branchen & Standorte","In den **Vereinigten Staaten** ist die Nachfrage nach **Maschinelles Lernen** in Schlüsselbranchen und strategischen Standorten besonders hoch. Zu den Top-Branchen gehören **Versicherung** ([Insurance](\u002Fjobs-by-industry\u002Finsurance)) und **Investment Management** ([Investment Management](\u002Fjobs-by-industry\u002Finvestment-management)), wo maschinelles Lernen für Risikomanagement, Kundenanalysen und Prozessoptimierung eingesetzt wird.\n\nBei den Standorten ragen **Alpharetta** ([Alpharetta](\u002Fjobs-in-alpharetta)), **Chicago** ([Chicago](\u002Fjobs-in-chicago)) und **Newport Beach** ([Newport Beach](\u002Fjobs-in-newport-beach)) hervor. **Alpharetta** ist ein aufstrebendes Technologiezentrum mit vielen FinTech-Unternehmen, die maschinelles Lernen für innovative Lösungen nutzen. **Chicago**, als globaler Finanzhub, bietet zahlreiche Möglichkeiten in Banken und Versicherungen, die diese Technologie für Handelsalgorithmen und Compliance einsetzen. **Newport Beach** hingegen ist bekannt für seine Investmentfirmen, die maschinelles Lernen zur Portfoliosteuerung und Marktprognose verwenden. Diese Standorte kombinieren Infrastruktur, Talentpool und Branchenvielfalt, um maschinelles Lernen voranzutreiben.",{"title":13,"content":14},"Gefragte Skills & Arbeitgeber","In den **Vereinigten Staaten** verlangen Top-Arbeitgeber wie **Allianz Insurance** und **Pacific Investment Mgt Co. LLC** nach **Maschinelles Lernen** in Verbindung mit spezifischen Expertisen. Dazu gehören **Risikomanagement** ([Risk Management](\u002Fjobs-by-expertise\u002Frisk-management)), **Schadenbearbeitung** ([Claims Handling](\u002Fjobs-by-expertise\u002Fclaims-handling)), **Kunden-Onboarding** ([Client Onboarding](\u002Fjobs-by-expertise\u002Fclient-onboarding)) und **Portfolioanalyse** ([Portfolio Analysis](\u002Fjobs-by-expertise\u002Fportfolio-analysis)). Diese Fähigkeiten ermöglichen es, maschinelles Lernen für praktische Anwendungen wie Betrugserkennung, Kundenbindung und Anlagestrategien zu nutzen.\n\nWeitere gefragte Expertisen sind **Aktuariatswissenschaft** ([Actuarial Science](\u002Fjobs-by-expertise\u002Factuarial-science)), **technische Preisgestaltung** ([Technical Pricing](\u002Fjobs-by-expertise\u002Ftechnical-pricing)) und **quantitative Forschung** ([Quantitative Research](\u002Fjobs-by-expertise\u002Fquantitative-research)), die in Versicherungs- und Investmentkontexten unverzichtbar sind. Arbeitgeber integrieren maschinelles Lernen in **Geschäftsprozessverbesserung** ([Business Process Improvement](\u002Fjobs-by-expertise\u002Fbusiness-process-improvement)) und **Kundenerlebnismanagement** ([Customer Experience Management](\u002Fjobs-by-expertise\u002Fcustomer-experience-management)), um Effizienz und Servicequalität zu steigern. Diese Kombination aus technischem Know-how und domänenspezifischem Wissen macht Fachkräfte in den **Vereinigten Staaten** besonders wertvoll.",{"title":16,"content":17},"Karriere & Entwicklung","Karrierewege mit **Maschinelles Lernen** in den **Vereinigten Staaten** sind vielfältig und erfordern eine Mischung aus IT-Fähigkeiten und branchenspezifischem Wissen. Typische Rollen umfassen Data Scientist, ML Engineer oder Quantitative Analyst in Branchen wie **Versicherung** ([Insurance](\u002Fjobs-by-industry\u002Finsurance)) und **Investment Management** ([Investment Management](\u002Fjobs-by-industry\u002Finvestment-management)). Um einzusteigen, sollten Interessenten **Künstliche Intelligenz** ([Artificial Intelligence](\u002Fjobs-by-skill\u002Fartificial-intelligence)), **Python** ([Python](\u002Fjobs-by-skill\u002Fpython)) und **Datenanalyse** ([Data Analysis](\u002Fjobs-by-skill\u002Fdata-analysis)) beherrschen, da diese Grundlagen für Modellentwicklung und -implementierung entscheidend sind.\n\nFortgeschrittene Fähigkeiten wie **Risikomodellierung** ([Risk Modeling](\u002Fjobs-by-expertise\u002Frisk-modeling)), **Finanzmodellierung** ([Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling)) und **Zeitreihenanalyse** ([Time Series Analysis](\u002Fjobs-by-expertise\u002Ftime-series-analysis)) sind in Verbindung mit Tools wie **Matlab** ([Matlab](\u002Fjobs-by-skill\u002Fmatlab)) und **Preisgestaltungstools** ([Pricing Tools](\u002Fjobs-by-skill\u002Fpricing-tools)) gefragt. Praktische Erfahrung durch Projekte oder Zertifizierungen in **Datenwissenschaft** ([Data Science](\u002Fjobs-by-skill\u002Fdata-science)) und **Programmierung** ([Programming](\u002Fjobs-by-skill\u002Fprogramming)) kann den Einstieg erleichtern. Kontinuierliches Lernen und Anpassung an neue Technologien sind essenziell, um in diesem dynamischen Feld in den **Vereinigten Staaten** erfolgreich zu sein.",{"tab1":19,"tab2":22,"tab3":25,"tab4":28},{"title":20,"content":21},"Strategic Importance","Machine learning has become strategically vital across the financial sector in the [United States](\u002Fsearch), transforming how institutions analyze data, manage risk, and optimize operations. In [investment management](\u002Fjobs-by-industry\u002Finvestment-management), ML algorithms enhance [portfolio analysis](\u002Fjobs-by-expertise\u002Fportfolio-analysis) and [asset allocation](\u002Fjobs-by-expertise\u002Fasset-allocation), enabling more precise predictions of market movements and better investment decisions. The [insurance](\u002Fjobs-by-industry\u002Finsurance) industry leverages ML for advanced [risk modeling](\u002Fjobs-by-expertise\u002Frisk-modeling), [claims handling](\u002Fjobs-by-expertise\u002Fclaims-handling), and [technical pricing](\u002Fjobs-by-expertise\u002Ftechnical-pricing), improving accuracy in underwriting and fraud detection. Companies like [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) and [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) are at the forefront, using ML to drive innovation in [financial markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) and [customer experience management](\u002Fjobs-by-expertise\u002Fcustomer-experience-management). As data volumes grow, ML's role in [financial analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis) and [business process improvement](\u002Fjobs-by-expertise\u002Fbusiness-process-improvement) ensures competitive advantage, making it indispensable for firms navigating complex [multinational business](\u002Fjobs-by-expertise\u002Fmultinational-business) environments in the U.S.",{"title":23,"content":24},"Top Industries & Locations","Machine learning expertise is highly sought after in key U.S. financial hubs and industries. Top locations include [Alpharetta](\u002Fjobs-in-alpharetta), a growing tech and finance corridor; [Chicago](\u002Fsearch), a major center for trading and [risk management](\u002Fjobs-by-expertise\u002Frisk-management); and [Newport Beach](\u002Fsearch), known for investment firms and [asset management](\u002Fjobs-by-industry\u002Fasset-management). In the [insurance](\u002Fjobs-by-industry\u002Finsurance) sector, ML drives innovations in [P&C insurance](\u002Fjobs-by-expertise\u002Fpc-insurance), [reserving](\u002Fjobs-by-expertise\u002Freserving), and [loss modeling](\u002Fjobs-by-expertise\u002Floss-modeling), with demand concentrated in regions with strong insurance presences. The [investment management](\u002Fjobs-by-industry\u002Finvestment-management) industry relies on ML for [portfolio optimization](\u002Fjobs-by-expertise\u002Fportfolio-optimization), [catastrophe analysis](\u002Fjobs-by-expertise\u002Fcatastrophe-analysis), and [alternative risk transfer](\u002Fjobs-by-expertise\u002Falternative-risk-transfer), particularly in coastal financial districts. These industries use ML to enhance [financial modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) and [market analysis](\u002Fjobs-by-expertise\u002Fmarket-analysis), supporting roles in [structured insurance](\u002Fjobs-by-expertise\u002Fstructured-insurance) and [underwriting support](\u002Fjobs-by-expertise\u002Funderwriting-support) across the [United States](\u002Fsearch).",{"title":26,"content":27},"In-Demand Skills & Employers","Leading U.S. employers like [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) and [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) seek professionals with machine learning skills paired with domain expertise. Key areas include [risk assessment](\u002Fjobs-by-expertise\u002Frisk-assessment), [financial engineering](\u002Fjobs-by-expertise\u002Ffinancial-engineering), and [quantitative research](\u002Fjobs-by-expertise\u002Fquantitative-research), where ML enhances [actuarial science](\u002Fjobs-by-expertise\u002Factuarial-science) and [econometrics](\u002Fjobs-by-expertise\u002Feconometrics). Expertise in [client onboarding](\u002Fjobs-by-expertise\u002Fclient-onboarding), [relationship management](\u002Fjobs-by-expertise\u002Frelationship-management), and [key account management](\u002Fjobs-by-expertise\u002Fkey-account-management) is valuable for roles integrating ML into [sales](\u002Fjobs-by-expertise\u002Fsales) and [marketing activities](\u002Fjobs-by-expertise\u002Fmarketing-activities). ML supports [process improvement](\u002Fjobs-by-expertise\u002Fprocess-improvement) in [claims service planning](\u002Fjobs-by-expertise\u002Fclaims-service-planning) and [policy structuring](\u002Fjobs-by-expertise\u002Fpolicy-structuring), while in investment contexts, it aids [asset pricing](\u002Fjobs-by-expertise\u002Fasset-pricing) and [portfolio theory](\u002Fjobs-by-expertise\u002Fportfolio-theory). These employers also value skills in [client analytics](\u002Fjobs-by-expertise\u002Fclient-analytics) and [management reporting](\u002Fjobs-by-expertise\u002Fmanagement-reporting), using ML to derive insights from [financial markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) data and drive [multinational business](\u002Fjobs-by-expertise\u002Fmultinational-business) strategies in the [United States](\u002Fsearch).",{"title":29,"content":30},"Career & Development","Career paths in machine learning within the U.S. financial sector often begin with roles in [data analysis](\u002Fjobs-by-skill\u002Fdata-analysis) or [financial analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis), progressing to specialized positions in [quantitative research](\u002Fjobs-by-expertise\u002Fquantitative-research) or [risk modeling](\u002Fjobs-by-expertise\u002Frisk-modeling). To build expertise, focus on mastering core IT skills like [Python](\u002Fjobs-by-skill\u002Fpython) for programming and [artificial intelligence](\u002Fjobs-by-skill\u002Fartificial-intelligence) tools, complemented by [Excel](\u002Fjobs-by-skill\u002Fms-excel) for data manipulation and [PowerPoint](\u002Fjobs-by-skill\u002Fms-powerpoint) for presenting insights. Learning [data science](\u002Fjobs-by-skill\u002Fdata-science) methodologies and using pricing tools or risk modeling software enhances capabilities in [financial modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) and [investment analysis](\u002Fjobs-by-expertise\u002Finvestment-analysis). Relevant expertise includes [time series analysis](\u002Fjobs-by-expertise\u002Ftime-series-analysis) for [financial markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) and [portfolio management](\u002Fjobs-by-expertise\u002Fportfolio-management) for [asset allocation](\u002Fjobs-by-expertise\u002Fasset-allocation). Professionals can advance by contributing to [research publication](\u002Fjobs-by-expertise\u002Fresearch-publication) or leading [business process improvement](\u002Fjobs-by-expertise\u002Fbusiness-process-improvement) initiatives, with opportunities in [actuarial science](\u002Fjobs-by-expertise\u002Factuarial-science) or [client analytics](\u002Fjobs-by-expertise\u002Fclient-analytics) across the [United States](\u002Fsearch).","skill:machine-learning:us","2026-08-17T09:02:32.814521+02:00",{"total":34,"jobs":35},51,[36,80,139,185,215,273,322,350,423,463,488,527,563,602,636,659,689,728,755,783],{"id":37,"slug":38,"title":39,"raw_title":40,"is_featured":41,"company":42,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":46,"processed_country_iso_code_gmaps":48,"processed_home_office":50,"processed_salary_min":51,"processed_salary_max":52,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":55,"processed_employment_types":57,"processed_it_skills":58,"processed_it_skills_labels":60,"processed_job_expertise_skills":63,"processed_job_expertise_skills_labels":66,"max_cpc":78,"actual_cpc":79},81990,"complex-claims-analyst-financial-lines-epl-mfd-allianz-insurance","Complex Claims Analyst - Financial Lines - EPL (m\u002Ff\u002Fd)",null,false,{"name":43,"slug":44,"logo_url":45},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",[47],"Alpharetta",[49],"US","hybrid",112818,170509,"USD","estimated",[56],"FULL_TIME","permanent",{"machine learning":59,"artificial intelligence":59},2,[61,62],"Artificial Intelligence","Machine Learning",{"reporting":64,"epl claims":65,"claims handling":65,"claims reserving":65,"claims settlement":65,"coverage analysis":65,"market management":64,"liability insurance":65,"claims investigation":65,"financial lines insurance":65,"legal and regulatory knowledge":65},3,4,[67,68,69,70,71,72,73,74,75,76,77],"Claims Handling","EPL Claims","Financial Lines Insurance","Liability Insurance","Coverage Analysis","Claims Investigation","Claims Reserving","Claims Settlement","Legal and Regulatory Knowledge","Market Management","Reporting",1,1.5,{"id":81,"slug":82,"title":83,"raw_title":40,"is_featured":41,"company":84,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":87,"processed_country_iso_code_gmaps":88,"processed_home_office":89,"processed_salary_min":90,"processed_salary_max":91,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":92,"processed_employment_types":57,"processed_it_skills":93,"processed_it_skills_labels":94,"processed_job_expertise_skills":117,"processed_job_expertise_skills_labels":118,"max_cpc":78,"actual_cpc":79},87378,"vp-ai-engineering-enterprise-sedgwick-claims-management-services-inc","VP AI Engineering - Enterprise",{"name":85,"slug":86,"logo_url":40},"Sedgwick Claims Management Services Inc.","sedgwick-claims-management-services-inc",[],[49],"remote",200000,300000,[56],{"aws":65,"db2":64,"rag":65,"sso":64,"apis":65,"llms":65,"rbac":64,"azure":65,"etl\u002Felt":65,"mainframe":64,"snowflake":65,"agentic ai":65,"sql server":64,"generative ai":65,"feature stores":65,"data permissions":64,"machine learning":65,"vector databases":65,"claude enterprise":65,"microsoft copilot":64,"chatgpt enterprise":65,"workflow automation":65,"cloud data platforms":65},[95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,62,116],"Snowflake","AWS","Azure","ETL\u002FELT","SQL Server","DB2","Mainframe","LLMs","Agentic AI","RAG","APIs","Workflow Automation","Vector Databases","Feature Stores","ChatGPT Enterprise","Claude Enterprise","Microsoft Copilot","SSO","RBAC","Data Permissions","Cloud Data Platforms","Generative AI",{"budgeting":65,"ai governance":65,"ai engineering":65,"cost governance":65,"data governance":65,"risk management":65,"roi measurement":65,"talent strategy":65,"data engineering":65,"vendor management":65,"license management":65,"succession planning":65,"technology strategy":65,"financial management":65,"security and privacy":65,"regulatory compliance":65,"enterprise integration":65,"enterprise architecture":65,"platform administration":65,"investment prioritization":65},[119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138],"Data Engineering","AI Engineering","Enterprise Architecture","Data Governance","AI Governance","Financial Management","Budgeting","Investment Prioritization","ROI Measurement","Vendor Management","License Management","Cost Governance","Regulatory Compliance","Security and Privacy","Talent Strategy","Succession Planning","Platform Administration","Enterprise Integration","Technology Strategy","Risk Management",{"id":140,"slug":141,"title":142,"raw_title":40,"is_featured":41,"company":143,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":146,"processed_country_iso_code_gmaps":148,"processed_home_office":149,"processed_salary_min":150,"processed_salary_max":151,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":152,"processed_employment_types":57,"processed_it_skills":153,"processed_it_skills_labels":154,"processed_job_expertise_skills":172,"processed_job_expertise_skills_labels":173,"max_cpc":78,"actual_cpc":79},87453,"ai-solutions-engineer-portsmouth-nh-service-federal-credit-union","AI Solutions Engineer - Portsmouth NH",{"name":144,"slug":145,"logo_url":40},"Service Federal Credit Union","service-federal-credit-union",[147],"Portsmouth",[49],"onsite",94960,118700,[56],{"sql":65,"devops":64,"python":65,"uipath":64,"rest apis":65,"javascript":65,"typescript":65,"generative ai":65,"microsoft azure":65,"semantic search":64,"data engineering":64,"machine learning":65,"vector databases":64,"azure ai services":65,"microsoft copilot":64,"prompt engineering":65,"automation anywhere":64,"business intelligence":64,"source control systems":64,"microsoft power automate":64,"robotic process automation":64,"model context protocol (mcp)":64},[155,156,157,158,159,160,161,162,163,164,165,166,107,167,168,111,62,116,169,170,119,171],"Python","JavaScript","TypeScript","SQL","Microsoft Azure","Azure AI services","REST APIs","Microsoft Power Automate","UiPath","Automation Anywhere","DevOps","Source Control Systems","Semantic Search","Model Context Protocol (MCP)","Prompt Engineering","Robotic Process Automation","Business Intelligence",{"data privacy":65,"ai governance":64,"generative ai":65,"data analytics":65,"reporting tools":64,"risk management":65,"machine learning":65,"security controls":65,"cloud technologies":65,"prompt engineering":65,"workflow automation":65,"predictive analytics":65,"dashboard development":64,"regulatory compliance":65,"artificial intelligence":65,"model context protocol (mcp)":64,"financial services regulations":65,"nist ai risk management framework":64,"enterprise application integration":65,"retrieval-augmented generation (rag)":65},[61,62,116,169,174,168,175,176,106,177,178,179,180,131,138,181,182,183,123,184],"Retrieval-Augmented Generation (RAG)","Enterprise Application Integration","Cloud Technologies","Data Analytics","Predictive Analytics","Dashboard Development","Reporting Tools","Data Privacy","Security Controls","Financial Services Regulations","NIST AI Risk Management Framework",{"id":186,"slug":187,"title":188,"raw_title":40,"is_featured":41,"company":189,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":190,"processed_country_iso_code_gmaps":191,"processed_home_office":149,"processed_salary_min":192,"processed_salary_max":193,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":194,"processed_employment_types":40,"processed_it_skills":195,"processed_it_skills_labels":196,"processed_job_expertise_skills":202,"processed_job_expertise_skills_labels":203,"max_cpc":78,"actual_cpc":79},87406,"senior-data-scientist-sedgwick-claims-management-services-inc","Senior Data Scientist",{"name":85,"slug":86,"logo_url":40},[],[49],120000,160000,[56],{"r":65,"sql":65,"python":65,"etl pipelines":65,"machine learning":65,"microsoft office":64,"data visualization tools":65,"natural language processing":64},[155,197,158,198,199,62,200,201],"R","Data Visualization Tools","ETL Pipelines","Natural Language Processing","Microsoft Office",{"data science":65,"model review":65,"data analysis":65,"data wrangling":65,"report writing":65,"healthcare data":64,"data exploration":65,"feature engineering":65,"predictive modeling":65,"supervised learning":65,"unsupervised learning":65},[204,205,206,207,208,209,210,211,212,213,214],"Predictive Modeling","Data Science","Data Analysis","Data Exploration","Data Wrangling","Feature Engineering","Supervised Learning","Unsupervised Learning","Model Review","Report Writing","Healthcare Data",{"id":216,"slug":217,"title":218,"raw_title":40,"is_featured":41,"company":219,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":222,"processed_country_iso_code_gmaps":224,"processed_home_office":149,"processed_salary_min":225,"processed_salary_max":226,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":227,"processed_employment_types":57,"processed_it_skills":228,"processed_it_skills_labels":229,"processed_job_expertise_skills":248,"processed_job_expertise_skills_labels":249,"max_cpc":78,"actual_cpc":79},85796,"engineering-senior-manager-fraud-technologies-manufacturers-and-traders-trust-co","Engineering Senior Manager, Fraud Technologies",{"name":220,"slug":221,"logo_url":40},"Manufacturers and Traders Trust Co","manufacturers-and-traders-trust-co",[223],"Buffalo",[49],167600,279400,[56],{"aiq":65,"sql":64,"java":64,"ci\u002Fcd":65,"falcon":65,"python":64,"feedzai":65,"actimize":65,"featurespace":65,"nice actimize":65,"cloud computing":65,"graph databases":64,"machine learning":65,"network analytics":64,"real-time analytics":65,"sas fraud management":65,"big data technologies":65,"infrastructure as code":65,"artificial intelligence":65,"event-driven architecture":65,"real-time event streaming":65,"site reliability engineering (sre)":65},[155,158,230,231,232,233,234,235,236,237,238,239,240,62,61,241,242,243,244,245,246,247],"Java","Cloud Computing","CI\u002FCD","Infrastructure as Code","Site Reliability Engineering (SRE)","Event-Driven Architecture","Real-Time Analytics","Big Data Technologies","Graph Databases","Network Analytics","Real-Time Event Streaming","Actimize","AIQ","Featurespace","Feedzai","Falcon","SAS Fraud Management","NICE Actimize",{"cybersecurity":65,"authentication":65,"agile practices":65,"fraud detection":65,"risk management":65,"fraud prevention":65,"budget management":65,"customer identity":65,"fraud decisioning":65,"vendor management":65,"project management":65,"strategic planning":65,"talent development":65,"workforce planning":65,"employee engagement":65,"fraud investigation":65,"succession planning":65,"technology governance":65,"operational excellence":65,"performance management":65,"platform modernization":65,"case management systems":65,"fraud operations support":65,"system development life cycle":65,"digital banking risk management":65,"real-time transaction processing":65},[250,251,252,253,138,254,255,256,257,258,259,260,261,262,134,263,128,264,265,266,267,268,269,270,271,272],"Fraud Prevention","Fraud Detection","Fraud Investigation","Fraud Decisioning","Real-Time Transaction Processing","Case Management Systems","Fraud Operations Support","Agile Practices","Budget Management","Strategic Planning","Workforce Planning","Performance Management","Talent Development","Employee Engagement","Technology Governance","Operational Excellence","Platform Modernization","System Development Life Cycle","Project Management","Customer Identity","Authentication","Cybersecurity","Digital Banking Risk Management",{"id":274,"slug":275,"title":276,"raw_title":40,"is_featured":41,"company":277,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":278,"processed_country_iso_code_gmaps":279,"processed_home_office":149,"processed_salary_min":280,"processed_salary_max":281,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":282,"processed_employment_types":57,"processed_it_skills":283,"processed_it_skills_labels":284,"processed_job_expertise_skills":304,"processed_job_expertise_skills_labels":305,"max_cpc":78,"actual_cpc":79},85800,"enterprise-architect-commercial-lending-manufacturers-and-traders-trust-co","Enterprise Architect - Commercial Lending",{"name":220,"slug":221,"logo_url":40},[223],[49],139700,232900,[56],{"afs":64,"fis":64,"apis":64,"ncino":64,"abrigo":64,"devops":59,"moody's":64,"bottomline":64,"jack henry":64,"salesforce":64,"generative ai":59,"microservices":64,"data platforms":64,"cloud computing":64,"data governance":64,"precisionlender":64,"machine learning":59,"workflow automation":59,"analytics enablement":64,"integration patterns":64,"data privacy standards":59,"master data management":64,"artificial intelligence":59,"cybersecurity principles":59,"architectural modeling tools":64,"secure architecture practices":59,"intelligent document processing":59},[231,285,105,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,61,116,62,301,106,122,302,303,165],"Microservices","Data Platforms","Integration Patterns","Cybersecurity Principles","Data Privacy Standards","Secure Architecture Practices","Architectural Modeling Tools","nCino","AFS","Bottomline","Salesforce","Moody's","FIS","PrecisionLender","Jack Henry","Abrigo","Intelligent Document Processing","Master Data Management","Analytics Enablement",{"it governance":64,"business acumen":65,"solution design":65,"data architecture":64,"vendor evaluation":64,"agile methodologies":64,"portfolio management":64,"value stream mapping":64,"regulatory compliance":64,"technology integration":65,"product operating model":65,"lending platform strategy":65,"business capability modeling":64,"commercial banking knowledge":65,"enterprise change management":64,"risk and compliance awareness":65,"enterprise architecture frameworks":65},[306,307,308,309,310,311,312,313,314,315,131,316,317,318,319,320,321],"Enterprise Architecture Frameworks","Solution Design","Technology Integration","Risk and Compliance Awareness","Business Acumen","Product Operating Model","Lending Platform Strategy","Commercial Banking Knowledge","Business Capability Modeling","Value Stream Mapping","IT Governance","Portfolio Management","Enterprise Change Management","Data Architecture","Vendor Evaluation","Agile Methodologies",{"id":323,"slug":324,"title":325,"raw_title":40,"is_featured":41,"company":326,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":329,"processed_country_iso_code_gmaps":331,"processed_home_office":149,"processed_salary_min":90,"processed_salary_max":332,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":333,"processed_employment_types":57,"processed_it_skills":334,"processed_it_skills_labels":335,"processed_job_expertise_skills":341,"processed_job_expertise_skills_labels":342,"max_cpc":78,"actual_cpc":79},86645,"risk-data-analytics-product-owner-reporting-lead-federal-reserve-bank-of-new-york","Risk Data Analytics Product Owner & Reporting Lead",{"name":327,"slug":328,"logo_url":40},"Federal Reserve Bank of New York","federal-reserve-bank-of-new-york",[330],"New York",[49],230000,[56],{"r":64,"python":65,"tableau":65,"power bi":65,"data modeling":65,"machine learning":64,"data visualization":65,"data analytics platforms":64},[336,337,155,197,338,339,62,340],"Tableau","Power BI","Data Modeling","Data Visualization","Data Analytics Platforms",{"reporting":65,"ai governance":64,"data analysis":65,"data strategy":64,"risk management":65,"dashboard design":65,"product ownership":65,"usability studies":64,"feature engineering":65,"user acceptance testing":64,"exploratory data analysis":65,"key risk indicators (kris)":65},[138,343,206,344,123,345,346,209,347,77,348,349],"Product Ownership","Key Risk Indicators (KRIs)","Data Strategy","Exploratory Data Analysis","Dashboard Design","User Acceptance Testing","Usability Studies",{"id":351,"slug":352,"title":353,"raw_title":40,"is_featured":41,"company":354,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":355,"processed_country_iso_code_gmaps":356,"processed_home_office":149,"processed_salary_min":225,"processed_salary_max":226,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":357,"processed_employment_types":57,"processed_it_skills":358,"processed_it_skills_labels":359,"processed_job_expertise_skills":371,"processed_job_expertise_skills_labels":372,"max_cpc":78,"actual_cpc":79},85797,"engineering-senior-manager-anti-money-laundering-aml-technologies-manufacturers-and-traders-trust-co","Engineering Senior Manager, Anti-Money Laundering (AML) Technologies",{"name":220,"slug":221,"logo_url":40},[223],[49],[56],{"ci\u002Fcd":65,"automation":65,"graph analytics":65,"word processing":64,"machine learning":65,"real-time monitoring":65,"presentation software":64,"infrastructure as code":65,"platform observability":65,"artificial intelligence":65,"spreadsheet applications":64,"cloud-native architectures":65,"data engineering platforms":65,"project management software":64,"enterprise integration patterns":65,"site reliability engineering (sre)":65},[360,361,362,232,233,234,363,364,61,62,365,366,367,368,369,370],"Cloud-native architectures","Data engineering platforms","Enterprise integration patterns","Platform observability","Automation","Graph analytics","Real-time monitoring","Project management software","Word processing","Presentation software","Spreadsheet applications",{"slos":65,"audit":65,"compliance":65,"cybersecurity":65,"platform slas":65,"data analytics":65,"investigations":65,"agile practices":65,"case management":65,"risk management":65,"financial crimes":65,"model validation":65,"aml risk modeling":65,"audit remediation":65,"budget management":65,"entity resolution":65,"network analytics":65,"vendor management":65,"service management":65,"strategic planning":65,"talent development":65,"workforce planning":65,"employee engagement":65,"operational metrics":65,"succession planning":65,"behavioral analytics":65,"regulatory reporting":65,"roadmap presentation":65,"watchlist monitoring":65,"customer risk scoring":65,"technology governance":65,"operational excellence":65,"performance management":65,"transaction monitoring":65,"aml technology strategy":65,"business plan awareness":65,"regulatory examinations":65,"false positive reduction":65,"financial crimes analytics":65,"anti-money laundering (aml)":65,"strategic objectives shaping":65,"technology budget management":65,"suspicious activity detection":65,"system development life cycle":65,"modernization of aml platforms":65,"strategic platform investments":65,"vendor relationship management":65,"enterprise architecture standards":65,"enterprise application development":65,"real-time monitoring and detection":65,"financial crime compliance functions":65,"investigator productivity improvement":65,"financial intelligence unit (fiu) support":65},[373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,271,177,396,239,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422],"Anti-Money Laundering (AML)","Financial Crimes","Transaction Monitoring","Customer Risk Scoring","Investigations","Case Management","Suspicious Activity Detection","Regulatory Reporting","Agile practices","Budget management","Vendor management","Strategic planning","Workforce planning","Performance management","Talent development","Succession planning","Employee engagement","Technology governance","Operational excellence","Service management","Risk management","Compliance","Audit","Financial Intelligence Unit (FIU) Support","Entity Resolution","Watchlist Monitoring","Behavioral Analytics","AML Risk Modeling","Financial Crimes Analytics","Model validation","Audit remediation","Regulatory examinations","System development life cycle","Enterprise application development","Platform SLAs","SLOs","Operational metrics","Modernization of AML platforms","False positive reduction","Investigator productivity improvement","Real-time monitoring and detection","AML technology strategy","Roadmap presentation","Vendor relationship management","Technology budget management","Strategic platform investments","Financial crime compliance functions","Enterprise architecture standards","Business plan awareness","Strategic objectives shaping",{"id":424,"slug":425,"title":426,"raw_title":40,"is_featured":41,"company":427,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":428,"processed_country_iso_code_gmaps":429,"processed_home_office":149,"processed_salary_min":430,"processed_salary_max":431,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":432,"processed_employment_types":57,"processed_it_skills":433,"processed_it_skills_labels":434,"processed_job_expertise_skills":445,"processed_job_expertise_skills_labels":446,"max_cpc":78,"actual_cpc":79},85952,"product-manager-iv-manufacturers-and-traders-trust-co","Product Manager IV",{"name":220,"slug":221,"logo_url":40},[330],[49],210125,215125,[56],{"etl":65,"sql":65,"apis":65,"appian":65,"power bi":65,"power apps":65,"sharepoint":65,"sql server":65,"forecasting":64,"power automate":65,"microsoft azure":65,"machine learning":64,"automation strategy":65,"predictive modeling":64,"digital transformation":65,"microsoft power platform":65,"low-code\u002Fno-code technologies":65},[99,159,158,435,436,437,438,337,439,105,440,62,204,441,442,443,444],"ETL","Microsoft Power Platform","Power Apps","Power Automate","Appian","SharePoint","Forecasting","Low-code\u002Fno-code technologies","Automation strategy","Digital transformation",{"sdlc":65,"cost structure":65,"market analysis":65,"product pricing":65,"risk management":65,"revenue planning":65,"business analysis":65,"data storytelling":65,"product management":65,"product development":65,"systems integration":65,"statistical modeling":64,"product profitability":65,"regulatory compliance":65,"strategic translation":65,"sales channel strategy":65,"product risk management":65,"technical product management":65},[447,448,449,450,451,452,453,454,455,131,138,456,457,458,459,460,461,462],"Product Management","Product Pricing","Cost Structure","Product Risk Management","Revenue Planning","Product Profitability","Sales Channel Strategy","Market Analysis","Product Development","Data Storytelling","Strategic Translation","Technical Product Management","SDLC","Systems Integration","Statistical Modeling","Business Analysis",{"id":464,"slug":465,"title":466,"raw_title":40,"is_featured":41,"company":467,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":470,"processed_country_iso_code_gmaps":472,"processed_home_office":50,"processed_salary_min":193,"processed_salary_max":473,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":474,"processed_employment_types":57,"processed_it_skills":475,"processed_it_skills_labels":476,"processed_job_expertise_skills":477,"processed_job_expertise_skills_labels":478,"max_cpc":78,"actual_cpc":79},86412,"pgim-quantitative-solutions-equity-research-director-pgim-quantitative-solutions-llc","PGIM Quantitative Solutions, Equity Research Director",{"name":468,"slug":469,"logo_url":40},"PGIM Quantitative Solutions LLC","pgim-quantitative-solutions-llc",[471],"Newark",[49],170000,[56],{"python":65,"machine learning":64,"artificial intelligence":64,"natural language processing":64},[155,62,61,200],{"asset pricing":65,"equity research":65,"security selection":65,"thought leadership":65,"client presentation":65,"dataset integration":65,"white paper authoring":65,"quantitative investing":65,"academic research evaluation":65},[479,480,481,482,483,484,485,486,487],"Quantitative Investing","Asset Pricing","Equity Research","Security Selection","Dataset Integration","White Paper Authoring","Client Presentation","Academic Research Evaluation","Thought Leadership",{"id":489,"slug":490,"title":491,"raw_title":40,"is_featured":41,"company":492,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":496,"processed_country_iso_code_gmaps":498,"processed_home_office":149,"processed_salary_min":499,"processed_salary_max":500,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":501,"processed_employment_types":57,"processed_it_skills":502,"processed_it_skills_labels":503,"processed_job_expertise_skills":507,"processed_job_expertise_skills_labels":508,"max_cpc":78,"actual_cpc":79},86370,"svp-marketing-technology-customer-lifecycle-strategy-pacific-investment-mgt-co-llc","SVP, Marketing Technology & Customer Lifecycle Strategy",{"name":493,"slug":494,"logo_url":495},"Pacific Investment Mgt Co. LLC","pacific-investment-mgt-co-llc","https:\u002F\u002Fupload.wikimedia.org\u002Fwikipedia\u002Fcommons\u002Fthumb\u002F4\u002F49\u002FPIMCO_Logo.svg\u002F330px-PIMCO_Logo.svg.png",[497],"Newport Beach",[49],250000,305000,[56],{"sql":64,"apis":64,"python":64,"crm systems":65,"generative ai":65,"analytics tools":65,"machine learning":65,"data architecture":65,"marketing automation platforms (adobe marketo engage, eloqua, salesforce marketing cloud, hubspot)":65},[155,158,504,505,105,319,62,116,506],"Marketing Automation Platforms (Adobe Marketo Engage, Eloqua, Salesforce Marketing Cloud, HubSpot)","CRM Systems","Analytics Tools",{"data quality":65,"segmentation":65,"ai governance":65,"roi analytics":65,"experimentation":65,"gdpr compliance":65,"personalization":65,"team leadership":65,"content strategy":65,"budget management":65,"vendor management":65,"causal measurement":65,"consent management":65,"data and analytics":65,"propensity scoring":65,"identity resolution":65,"predictive modeling":65,"privacy regulations":65,"marketing automation":65,"marketing technology":65,"regulatory compliance":65,"digital transformation":65,"measurement frameworks":65},[509,510,511,512,204,513,514,515,516,517,518,519,520,521,128,258,522,523,524,525,526,123,131],"Marketing Technology","Digital Transformation","Data and Analytics","Segmentation","Propensity Scoring","Experimentation","Causal Measurement","ROI Analytics","Identity Resolution","Data Quality","Consent Management","GDPR Compliance","Privacy Regulations","Team Leadership","Marketing Automation","Personalization","Content Strategy","Measurement Frameworks",{"id":528,"slug":529,"title":530,"raw_title":40,"is_featured":41,"company":531,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":534,"processed_country_iso_code_gmaps":536,"processed_home_office":50,"processed_salary_min":90,"processed_salary_max":537,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":538,"processed_employment_types":57,"processed_it_skills":539,"processed_it_skills_labels":540,"processed_job_expertise_skills":551,"processed_job_expertise_skills_labels":552,"max_cpc":78,"actual_cpc":79},80595,"vp-head-of-engineering-practice-arch-insurance-group-inc","VP, Head of Engineering Practice",{"name":532,"slug":533,"logo_url":40},"Arch Insurance Group Inc.","arch-insurance-group-inc",[535],"Jersey City",[49],311000,[56],{"ai":64,"java":65,"ci\u002Fcd":65,"genai":64,"devops":65,"docker":65,"angular":65,"kubernetes":65,"spring boot":65,"observability":65,"microsoft azure":65,"machine learning":64,"automated testing":65,"relational databases":65,"non-relational databases":65},[230,541,542,543,544,159,545,546,165,232,547,548,549,550,62],"Spring Boot","Angular","Relational Databases","Non-relational Databases","Docker","Kubernetes","Automated Testing","Observability","AI","GenAI",{"microservices":65,"api-first design":65,"engineering strategy":65,"insurance p&c domain":64,"software engineering":65,"architecture decisions":65,"engineering governance":65,"full-stack development":65,"cloud-native architectures":65,"event-driven architectures":65,"engineering policies and standards":65},[553,554,555,285,556,557,558,559,560,561,562],"Software Engineering","Cloud-native Architectures","API-first Design","Event-driven Architectures","Engineering Strategy","Engineering Governance","Engineering Policies and Standards","Architecture Decisions","Full-stack Development","Insurance P&C Domain",{"id":564,"slug":565,"title":566,"raw_title":40,"is_featured":41,"company":567,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":570,"processed_country_iso_code_gmaps":572,"processed_home_office":149,"processed_salary_min":573,"processed_salary_max":574,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":575,"processed_employment_types":57,"processed_it_skills":576,"processed_it_skills_labels":577,"processed_job_expertise_skills":589,"processed_job_expertise_skills_labels":590,"max_cpc":78,"actual_cpc":79},86650,"ai-solutions-engineer-erp-systems-federal-reserve-bank-of-richmond","AI Solutions Engineer - ERP Systems",{"name":568,"slug":569,"logo_url":40},"Federal Reserve Bank of Richmond","federal-reserve-bank-of-richmond",[571],"Richmond",[49],133000,183000,[56],{"aws":64,"gcp":64,"sql":64,"llms":65,"saml":64,"azure":64,"ci\u002Fcd":64,"oauth":64,"devops":64,"python":65,"sap btp":64,"workday":64,"chatbots":65,"ai agents":65,"sap ariba":64,"restful apis":64,"generative ai":65,"data pipelines":64,"workday extend":64,"machine learning":65},[155,158,578,579,580,232,165,96,97,581,62,116,102,582,583,584,585,586,587,588],"RESTful APIs","OAuth","SAML","GCP","AI Agents","Chatbots","Workday","SAP Ariba","SAP BTP","Workday Extend","Data Pipelines",{"erp systems":65,"integration":64,"data management":64,"process automation":64,"production support":64,"project management":64,"technology assessment":64,"ai solution deployment":65,"security and governance":64,"technical documentation":64,"cloud platform engineering":65,"platform-as-a-service (paas)":65},[591,592,593,594,595,268,596,597,598,599,600,601],"AI Solution Deployment","Cloud Platform Engineering","ERP Systems","Platform-as-a-Service (PaaS)","Technical Documentation","Technology Assessment","Process Automation","Data Management","Integration","Security and Governance","Production Support",{"id":603,"slug":604,"title":605,"raw_title":40,"is_featured":41,"company":606,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":610,"processed_country_iso_code_gmaps":612,"processed_home_office":50,"processed_salary_min":613,"processed_salary_max":192,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":614,"processed_employment_types":57,"processed_it_skills":615,"processed_it_skills_labels":616,"processed_job_expertise_skills":622,"processed_job_expertise_skills_labels":623,"max_cpc":78,"actual_cpc":79},80418,"trader-american-century-investment-management-inc","Trader",{"name":607,"slug":608,"logo_url":609},"American Century Investment Management, Inc.","american-century-investment-management-inc","https:\u002F\u002Fupload.wikimedia.org\u002Fwikipedia\u002Fcommons\u002Fthumb\u002Fb\u002Fbd\u002FAmerican_Century_Investments_Logo.svg\u002F320px-American_Century_Investments_Logo.svg.png",[611],"Kansas City",[49],80000,[56],{"ems":64,"oms":64,"excel":65,"ai tools":64,"bloomberg":64,"machine learning":64},[617,618,62,619,620,621],"Excel","AI tools","Bloomberg","OMS","EMS",{"etf trading":65,"order management":65,"portfolio trading":65,"electronic trading":65,"algorithmic trading":65,"derivatives trading":65,"quantitative analysis":65,"equity market structure":65,"global equities trading":65,"foreign currency trading":65,"trading tools development":64,"capital markets coordination":65},[624,625,626,627,628,629,630,631,632,633,634,635],"Electronic Trading","Equity Market Structure","Global Equities Trading","ETF Trading","Foreign Currency Trading","Derivatives Trading","Portfolio Trading","Algorithmic Trading","Quantitative Analysis","Capital Markets Coordination","Order Management","Trading Tools Development",{"id":637,"slug":638,"title":639,"raw_title":40,"is_featured":41,"company":640,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":643,"processed_country_iso_code_gmaps":645,"processed_home_office":149,"processed_salary_min":646,"processed_salary_max":647,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":648,"processed_employment_types":57,"processed_it_skills":649,"processed_it_skills_labels":650,"processed_job_expertise_skills":652,"processed_job_expertise_skills_labels":653,"max_cpc":78,"actual_cpc":79},81091,"data-analyst-bmo-bank-na","Data Analyst",{"name":641,"slug":642,"logo_url":40},"BMO Bank N.A.","bmo-bank-na",[644],"Chicago",[49],65000,140000,[56],{"r":64,"sql":64,"python":64,"deep learning":65,"machine learning":65,"big data technologies":64,"data visualization tools":64},[155,158,197,62,651,237,198],"Deep Learning",{"statistics":64,"mathematics":64,"data wrangling":64,"risk management":64,"data preprocessing":64,"operations research":64,"predictive modeling":65,"ai\u002Fml solution assessment":64},[654,655,656,208,657,204,658,138],"Mathematics","Statistics","Operations Research","Data Preprocessing","AI\u002FML Solution Assessment",{"id":660,"slug":661,"title":662,"raw_title":40,"is_featured":41,"company":663,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":666,"processed_country_iso_code_gmaps":667,"processed_home_office":149,"processed_salary_min":668,"processed_salary_max":668,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":669,"processed_employment_types":57,"processed_it_skills":670,"processed_it_skills_labels":671,"processed_job_expertise_skills":676,"processed_job_expertise_skills_labels":677,"max_cpc":78,"actual_cpc":79},81035,"2027-blackstone-real-estate-acquisitions-analyst-blackstone-real-estate-advisors-lp","2027 Blackstone Real Estate Acquisitions Analyst",{"name":664,"slug":665,"logo_url":40},"Blackstone Real Estate Advisors LP","blackstone-real-estate-advisors-lp",[330],[49],110000,[56],{"sql":64,"apis":64,"excel":65,"python":64,"ai agents":64,"databases":64,"automation tools":64,"machine learning":64,"retrieval workflows":64,"large language models":64},[155,158,617,672,62,582,673,674,105,675],"Large Language Models","Retrieval Workflows","Automation Tools","Databases",{"finance":64,"economics":64,"accounting":64,"lbo modeling":65,"data analysis":64,"deal sourcing":64,"due diligence":64,"market research":64,"financial modeling":65,"legal negotiations":59,"quantitative analysis":65,"real estate valuation":64,"investment committee presentations":64},[678,679,680,681,682,632,683,206,684,685,686,687,688],"Accounting","Finance","Economics","Real Estate Valuation","Financial Modeling","Market Research","Due Diligence","Legal Negotiations","Investment Committee Presentations","LBO Modeling","Deal Sourcing",{"id":690,"slug":691,"title":605,"raw_title":40,"is_featured":41,"company":692,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":695,"processed_country_iso_code_gmaps":696,"processed_home_office":149,"processed_salary_min":90,"processed_salary_max":697,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":698,"processed_employment_types":57,"processed_it_skills":699,"processed_it_skills_labels":700,"processed_job_expertise_skills":707,"processed_job_expertise_skills_labels":708,"max_cpc":78,"actual_cpc":79},83051,"trader-5006-deutsche-bank-securities-inc",{"name":693,"slug":694,"logo_url":40},"5006 Deutsche Bank Securities Inc.","5006-deutsche-bank-securities-inc",[330],[49],307500,[56],{"vba":64,"excel":65,"intex":64,"python":65,"bloomberg":65,"bloomberg apis":64,"machine learning":64,"python dataframes":65,"monte carlo simulation":64,"bloomberg bond and swap pricers":64},[617,619,701,155,62,702,703,704,705,706],"VBA","Monte Carlo Simulation","Python DataFrames","Bloomberg APIs","Bloomberg Bond and Swap Pricers","Intex",{"econometrics":64,"dtc settlement":64,"risk management":65,"trade execution":65,"linear regression":64,"repo transactions":65,"structured credit":65,"swap transactions":65,"cash flow modeling":65,"derivative pricing":65,"financial modeling":65,"hedging strategies":65,"basel iii framework":64,"black-scholes model":65,"discounted cash flow":65,"euroclear settlement":64,"optimization methods":64,"regulatory compliance":64,"hybrid derivative products":65,"bank balance sheet mechanics":64,"financial time series analysis":64,"structuring complex transactions":65},[709,138,682,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,131,725,726,727],"Hedging Strategies","Derivative Pricing","Discounted Cash Flow","Black-Scholes Model","Financial Time Series Analysis","Optimization Methods","Econometrics","Linear Regression","Structuring Complex Transactions","Repo Transactions","Swap Transactions","Structured Credit","Hybrid Derivative Products","Cash Flow Modeling","Basel III Framework","Bank Balance Sheet Mechanics","DTC Settlement","Euroclear Settlement","Trade Execution",{"id":729,"slug":730,"title":731,"raw_title":40,"is_featured":41,"company":732,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":735,"processed_country_iso_code_gmaps":737,"processed_home_office":50,"processed_salary_min":738,"processed_salary_max":739,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":740,"processed_employment_types":57,"processed_it_skills":741,"processed_it_skills_labels":742,"processed_job_expertise_skills":745,"processed_job_expertise_skills_labels":746,"max_cpc":78,"actual_cpc":79},88463,"senior-data-scientist-customer-experience-genai-travelers-indemnity-co","Senior Data Scientist - Customer Experience GenAI",{"name":733,"slug":734,"logo_url":40},"Travelers Indemnity Co","travelers-indemnity-co",[736],"Hartford",[49],146400,241600,[56],{"r":64,"sql":64,"python":65,"deep learning":64,"generative ai":65,"computer vision":64,"machine learning":65,"data visualization":64,"statistical software":65,"natural language processing":64},[155,197,158,116,62,651,200,743,744,339],"Computer Vision","Statistical Software",{"regression":65,"fine-tuning":64,"data analysis":65,"deep learning":64,"generative ai":65,"rag pipelines":65,"classification":65,"machine vision":64,"value creation":64,"prompt engineering":65,"predictive modeling":65,"statistical modeling":65,"business intelligence":64,"business model concepts":64,"hallucination mitigation":64,"natural language processing":64},[116,747,748,749,200,651,461,204,171,206,169,750,751,752,753,754],"Regression","Classification","Machine Vision","RAG Pipelines","Fine-tuning","Hallucination Mitigation","Value Creation","Business Model Concepts",{"id":756,"slug":757,"title":758,"raw_title":40,"is_featured":41,"company":759,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":762,"processed_country_iso_code_gmaps":764,"processed_home_office":50,"processed_salary_min":765,"processed_salary_max":766,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":767,"processed_employment_types":768,"processed_it_skills":769,"processed_it_skills_labels":770,"processed_job_expertise_skills":775,"processed_job_expertise_skills_labels":776,"max_cpc":78,"actual_cpc":79},86665,"2027-summer-internship-business-technology-federal-reserve-bank-of-st-louis","2027 Summer Internship - Business Technology",{"name":760,"slug":761,"logo_url":40},"Federal Reserve Bank of St. Louis","federal-reserve-bank-of-st-louis",[763],"St. Louis",[49],36400,40040,[56],"temporary",{"r":64,"sql":64,"jira":59,"genai":59,"python":64,"ai tools":59,"confluence":59,"machine learning":59,"amazon web services":59},[155,197,158,771,772,773,774,62,550],"Jira","Confluence","Amazon Web Services","AI Tools",{"scrum":59,"banking":59,"economics":59,"statistics":64,"data science":64,"data analysis":64,"data matching":59,"documentation":64,"policy analysis":59,"product ownership":59,"security compliance":59},[206,205,343,777,778,655,779,780,680,781,782],"Scrum","Security Compliance","Policy Analysis","Banking","Documentation","Data Matching",{"id":784,"slug":785,"title":786,"raw_title":40,"is_featured":41,"company":787,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":788,"processed_country_iso_code_gmaps":789,"processed_home_office":149,"processed_salary_min":647,"processed_salary_max":473,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":790,"processed_employment_types":57,"processed_it_skills":791,"processed_it_skills_labels":792,"processed_job_expertise_skills":800,"processed_job_expertise_skills_labels":801,"max_cpc":78,"actual_cpc":79},76886,"data-architect-federal-reserve-bank-of-st-louis","Data Architect",{"name":760,"slug":761,"logo_url":40},[763],[49],[56],{"ai":59,"aws":64,"sql":65,"postgresql":65,"machine learning":59,"data modeling tools":65,"cloud data platforms":65,"big data technologies":64,"data catalog platforms":64,"data warehousing tools":64,"distributed query engines":64,"metadata management platforms":64,"large-scale data processing systems":64},[793,158,96,115,794,795,237,62,549,796,797,798,799],"PostgreSQL","Data Modeling Tools","Data Warehousing Tools","Data Catalog Platforms","Metadata Management Platforms","Distributed Query Engines","Large-scale Data Processing Systems",{"caching":65,"dataops":65,"encryption":65,"auditability":65,"data security":65,"access control":65,"data governance":65,"database design":65,"data engineering":65,"time-series data":64,"data architecture":65,"economic datasets":59,"public data access":59,"retention policies":65,"analytical datasets":64,"data classification":65,"data access patterns":65,"partitioning strategies":65,"data privacy regulations":65,"data integration patterns":65,"data lifecycle management":65,"data storage technologies":65,"research data environments":59},[319,119,802,122,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821],"Database Design","Data Security","DataOps","Data Privacy Regulations","Data Lifecycle Management","Data Integration Patterns","Data Storage Technologies","Partitioning Strategies","Caching","Data Access Patterns","Data Classification","Access Control","Encryption","Retention Policies","Auditability","Time-series Data","Analytical Datasets","Economic Datasets","Research Data Environments","Public Data Access",{"industry":823,"employment_type":861,"expertise_skills":870,"it_skills":930,"salary_currency":995,"processed_working_hours":1000},[824,828,832,835,838,840,843,846,849,852,855,858],{"key":825,"label":826,"count":827},"financial services","Financial Services",24,{"key":829,"label":830,"count":831},"insurance","Insurance",19,{"key":833,"label":780,"count":834},"banking",10,{"key":836,"label":837,"count":64},"financial markets infrastructure","Financial Markets Infrastructure",{"key":839,"label":138,"count":59},"risk management",{"key":841,"label":842,"count":59},"data","Data",{"key":844,"label":845,"count":78},"alternative asset management","Alternative Asset Management",{"key":847,"label":848,"count":78},"reinsurance","Reinsurance",{"key":850,"label":851,"count":78},"asset management","Asset Management",{"key":853,"label":854,"count":78},"credit union","Credit Union",{"key":856,"label":857,"count":78},"data provider","Data Provider",{"key":859,"label":860,"count":78},"real estate private equity","Real Estate Private Equity",[862,865,868],{"key":57,"label":863,"count":864},"PERMANENT",47,{"key":866,"label":867,"count":59},"student","STUDENT",{"key":768,"label":869,"count":78},"TEMPORARY",[871,874,877,879,883,887,889,892,895,897,899,902,905,907,909,911,913,915,917,919,921,923,925,928],{"key":872,"label":131,"slug":872,"count":873},"regulatory-compliance",14,{"key":875,"label":138,"slug":875,"count":876},"risk-management",12,{"key":878,"label":206,"slug":878,"count":834},"data-analysis",{"key":880,"label":881,"slug":880,"count":882},"project-management","Project management",8,{"key":884,"label":885,"slug":884,"count":886},"risk-assessment","Risk Assessment",7,{"key":888,"label":258,"slug":888,"count":886},"budget-management",{"key":890,"label":122,"slug":890,"count":891},"data-governance",6,{"key":893,"label":128,"slug":893,"count":894},"vendor-management",5,{"key":896,"label":394,"slug":896,"count":894},"compliance",{"key":898,"label":259,"slug":898,"count":894},"strategic-planning",{"key":900,"label":901,"slug":900,"count":894},"ai-governance","Ai Governance",{"key":903,"label":904,"slug":903,"count":65},"software-development","Software Development",{"key":906,"label":208,"slug":906,"count":65},"data-wrangling",{"key":908,"label":204,"slug":908,"count":65},"predictive-modeling",{"key":910,"label":271,"slug":910,"count":65},"cybersecurity",{"key":912,"label":134,"slug":912,"count":65},"succession-planning",{"key":914,"label":119,"slug":914,"count":65},"data-engineering",{"key":916,"label":317,"slug":916,"count":65},"portfolio-management",{"key":918,"label":265,"slug":918,"count":64},"operational-excellence",{"key":920,"label":261,"slug":920,"count":64},"performance-management",{"key":922,"label":345,"slug":922,"count":64},"data-strategy",{"key":924,"label":262,"slug":924,"count":64},"talent-development",{"key":926,"label":927,"slug":926,"count":64},"system-analysis","System Analysis",{"key":929,"label":251,"slug":929,"count":64},"fraud-detection",[931,933,936,939,943,946,950,953,955,957,961,964,966,969,971,974,976,979,982,984,986,988,991,993],{"key":932,"label":62,"slug":932,"count":34},"machine-learning",{"key":934,"label":155,"slug":934,"count":935},"python",27,{"key":937,"label":158,"slug":937,"count":938},"sql",18,{"key":940,"label":941,"slug":940,"count":942},"ai","Ai",13,{"key":944,"label":945,"slug":944,"count":876},"ms-azure","MS Azure",{"key":947,"label":948,"slug":947,"count":949},"generative-ai","Generative Ai",11,{"key":951,"label":952,"slug":951,"count":949},"aws","Aws",{"key":954,"label":61,"slug":954,"count":834},"artificial-intelligence",{"key":956,"label":230,"slug":956,"count":834},"java",{"key":958,"label":959,"slug":958,"count":960},"cicd","Ci\u002FCd",9,{"key":962,"label":963,"slug":962,"count":886},"devops","Devops",{"key":965,"label":197,"slug":965,"count":886},"r",{"key":967,"label":968,"slug":967,"count":894},"apis","Apis",{"key":970,"label":545,"slug":970,"count":894},"docker",{"key":972,"label":973,"slug":972,"count":894},"ms-excel","MS Excel",{"key":975,"label":651,"slug":975,"count":894},"deep-learning",{"key":977,"label":978,"slug":977,"count":894},"ms-powerbi","MS PowerBI",{"key":980,"label":981,"slug":980,"count":65},"git","Git",{"key":983,"label":107,"slug":983,"count":65},"vector-databases",{"key":985,"label":546,"slug":985,"count":65},"kubernetes",{"key":987,"label":548,"slug":987,"count":65},"observability",{"key":989,"label":990,"slug":989,"count":65},"restful-apis","Restful Apis",{"key":992,"label":177,"slug":992,"count":65},"data-analytics",{"key":994,"label":339,"slug":994,"count":65},"data-visualization",[996,998],{"key":53,"label":53,"count":997},50,{"key":999,"label":999,"count":78},"GBP",[1001],{"key":56,"label":56,"count":34},{"total":1003,"jobs":1004},0,[]]