[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-expertise-machine-learning-us":3,"job-search-\u002Fde-us\u002Fjobs-by-expertise\u002Fmachine-learning":33,"expertise-filters-\u002Fde-us\u002Fjobs-by-expertise\u002Fmachine-learning":699,"featured-jobs-\u002Fde-us\u002Fjobs-by-expertise\u002Fmachine-learning":859},{"image_path":4,"content_de":5,"content_en":18,"composite_key":31,"last_updated":32},"\u002Fimages\u002Fexpertise\u002Fmachine-learning.webp",{"tab1":6,"tab2":9,"tab3":12,"tab4":15},{"title":7,"content":8},"Bedeutung & Relevanz","Maschinelles Lernen hat sich zu einer Schlüsseltechnologie in den **Vereinigten Staaten** entwickelt, die die Finanzindustrie grundlegend verändert. Im Bereich **[Asset Management](\u002Fjobs-by-industry\u002Fasset-management)** ermöglicht **[Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning)** die Analyse riesiger Datenmengen für bessere Anlageentscheidungen und Risikoprognosen. Führende Unternehmen wie **CM003 American Century Services, LLC** und **Pacific Investment Mgt Co. LLC** setzen bereits intensiv auf diese Technologie.\n\nDie Relevanz zeigt sich besonders in der Automatisierung komplexer Prozesse wie **[Portfolio Management](\u002Fjobs-by-expertise\u002Fportfolio-management)** und **[Risk Management](\u002Fjobs-by-expertise\u002Frisk-management)**. Durch den Einsatz von **[Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai)** und **[Artificial Intelligence Tools](\u002Fjobs-by-skill\u002Fartificial-intelligence-tools)** können Finanzinstitute Muster in Marktdaten erkennen, die dem menschlichen Auge verborgen bleiben. Dies führt zu präziseren Vorhersagen und effizienteren Handelsstrategien.\n\nIm Versicherungssektor revolutioniert **[Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning)** die Schadensanalyse und Prämienkalkulation. Unternehmen wie **Allianz Insurance** nutzen Algorithmen für **[Financial Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis)** und Betrugserkennung. Die Technologie unterstützt zudem bei regulatorischen Anforderungen durch automatisierte **[Financial Reporting](\u002Fjobs-by-expertise\u002Ffinancial-reporting)** und Compliance-Überwachung.",{"title":10,"content":11},"Top-Branchen & Standorte","Die Nachfrage nach **[Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning)**-Expertise konzentriert sich in den **Vereinigten Staaten** auf mehrere Schlüsselstandorte und Branchen. In **Kansas City** haben sich insbesondere Unternehmen des **[Asset Management](\u002Fjobs-by-industry\u002Fasset-management)** etabliert, die fortschrittliche Algorithmen für **[Portfolio Management](\u002Fjobs-by-expertise\u002Fportfolio-management)** entwickeln.\n\n**Chicago** als traditionelles Finanzzentrum bietet zahlreiche Möglichkeiten in **[Banking](\u002Fjobs-by-industry\u002Fbanking)** und **[Investment Management](\u002Fjobs-by-industry\u002Fasset-management-investment-management)**, wo **[Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning)** für Handelsstrategien und Risikomanagement eingesetzt wird. Die Stadt ist ein Hotspot für Fintech-Innovationen.\n\nIn **Newport Beach** dominieren Unternehmen des **[Asset Management Financial Services](\u002Fjobs-by-industry\u002Fasset-management-financial-services)**, die komplexe quantitative Modelle entwickeln. Der Versicherungssektor zeigt ebenfalls starkes Interesse, besonders für **[Actuarial Analysis](\u002Fjobs-by-expertise\u002Factuarial-analysis)** und Schadensvorhersage.\n\nWeitere bedeutende Branchen umfassen **[Financial Services](\u002Fjobs-by-industry\u002Fasset-managementfinancial-services)** mit Fokus auf **[Systematic Trading](\u002Fjobs-by-expertise\u002Fsystematic-trading)** und **[Financial Engineering](\u002Fjobs-by-expertise\u002Ffinancial-engineering)**. Die Technologie findet zunehmend Anwendung in **[Property & Casualty Insurance](\u002Fjobs-by-expertise\u002Fproperty-casualty-insurance)** für präzisere Risikobewertungen.",{"title":13,"content":14},"Gefragte Skills & Arbeitgeber","Führende Arbeitgeber in den **Vereinigten Staaten** wie **CM003 American Century Services, LLC**, **Allianz Insurance** und **Pacific Investment Mgt Co. LLC** suchen nach Experten mit **[Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning)**-Kenntnissen kombiniert mit spezifischem Fachwissen.\n\nGefragte Expertise umfasst **[Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling)** für die Entwicklung prädiktiver Modelle, **[Quantitative Research](\u002Fjobs-by-expertise\u002Fquantitative-research)** für Handelsstrategien und **[Data Analysis](\u002Fjobs-by-expertise\u002Fdata-analysis)** für Marktprognosen. Kenntnisse in **[Risk Assessment](\u002Fjobs-by-expertise\u002Frisk-assessment)** sind essentiell für regulatorische Anforderungen.\n\nIm technischen Bereich werden **[Python](\u002Fjobs-by-skill\u002Fpython)** und **[SQL](\u002Fjobs-by-skill\u002Fsql)** für Datenverarbeitung, **[Java](\u002Fjobs-by-skill\u002Fjava)** für skalierbare Systeme und **[R](\u002Fjobs-by-skill\u002Fr)** für statistische Analysen benötigt. Cloud-Kenntnisse in **[AWS](\u002Fjobs-by-skill\u002Faws)** und Erfahrung mit **[Kubernetes](\u002Fjobs-by-skill\u002Fkubernetes)** sind zunehmend wichtig.\n\nWeitere relevante Fähigkeiten umfassen **[Time-Series Analysis](\u002Fjobs-by-expertise\u002Ftime-series-analysis)** für Finanzdaten, **[Natural Language Processing](\u002Fjobs-by-expertise\u002Fnatural-language-processing)** für Nachrichtenanalyse und **[Pattern Recognition](\u002Fjobs-by-expertise\u002Fpattern-recognition)** für Handelssignale. Tools wie **FactSet** und **Bloomberg** ergänzen die technische Ausstattung.",{"title":16,"content":17},"Karriere & Entwicklung","Karrierewege mit **[Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning)** in den **Vereinigten Staaten** bieten vielfältige Entwicklungsmöglichkeiten. Einstiegspositionen wie **Data Scientist** oder **Quantitative Analyst** führen zu Rollen wie **Machine Learning Engineer** oder **AI Research Lead** in führenden Finanzinstituten.\n\nFür den Erfolg sind fundierte Kenntnisse in **[Python](\u002Fjobs-by-skill\u002Fpython)** und **[SQL](\u002Fjobs-by-skill\u002Fsql)** essentiell, ergänzt durch **[Relational Databases](\u002Fjobs-by-skill\u002Frelational-databases)** und **[Object-Oriented Programming](\u002Fjobs-by-skill\u002Fobject-oriented-programming)**. Fortgeschrittene Themen wie **[Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai)** und **[Artificial Intelligence Tools](\u002Fjobs-by-skill\u002Fartificial-intelligence-tools)** öffnen Türen zu innovativen Projekten.\n\nPraktische Erfahrung mit **[Financial Markets](\u002Fjobs-by-expertise\u002Ffinancial-markets)** und **[Investment Strategy](\u002Fjobs-by-expertise\u002Finvestment-strategy)** ist ebenso wichtig wie technisches Verständnis von **[Cloud\u002FAWS](\u002Fjobs-by-skill\u002Fcloud-aws)** und **[CI\u002FCD](\u002Fjobs-by-skill\u002Fci-cd)**-Prozessen. Spezialisierungen in **[Portfolio Construction](\u002Fjobs-by-expertise\u002Fportfolio-construction)** oder **[Alpha Signal Development](\u002Fjobs-by-expertise\u002Falpha-signal-development)** bieten Wettbewerbsvorteile.\n\nWeiterbildungen sollten **[Statistics](\u002Fjobs-by-skill\u002Fstatistics)** und **[Probability](\u002Fjobs-by-skill\u002Fprobability)** vertiefen, kombiniert mit domänenspezifischem Wissen in **[IFRS 4](\u002Fjobs-by-expertise\u002Fifrs-4)** und **[IFRS 17](\u002Fjobs-by-expertise\u002Fifrs-17)** für Versicherungsanwendungen. Agile Methoden wie **[Agile\u002FSAFe](\u002Fjobs-by-skill\u002Fagile-safe)** runden das Profil ab.",{"tab1":19,"tab2":22,"tab3":25,"tab4":28},{"title":20,"content":21},"Strategic Importance","Machine Learning has become a transformative force in the United States financial sector, driving innovation across asset management, insurance, and investment management. In the competitive landscape of American financial services, ML algorithms enable firms to analyze vast datasets for predictive insights, automate complex processes, and enhance decision-making capabilities. Leading companies like [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) and [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) leverage ML for everything from risk assessment to portfolio optimization, giving them significant competitive advantages. The strategic importance extends beyond operational efficiency to revenue generation through algorithmic trading strategies and personalized financial product recommendations. As regulatory requirements like IFRS 17 and quarterly closing demand more sophisticated analysis, ML provides the computational power to meet these challenges while maintaining compliance. Financial institutions across the United States are investing heavily in ML capabilities, recognizing that mastery of this technology is no longer optional but essential for market leadership and sustainable growth in today's data-driven economy.",{"title":23,"content":24},"Top Industries & Locations","Machine Learning expertise is particularly sought after in key American financial hubs and specialized sectors. In the [Asset Management](\u002Fjobs-by-industry\u002Fasset-management) and [Banking](\u002Fjobs-by-industry\u002Fbanking) industries, ML drives alpha generation and risk management strategies, while the insurance sector uses it for predictive modeling and claims analysis. Major demand centers include [Kansas City](\u002Fjobs-in-kansas-city), home to [CM003 American Century Services, LLC](\u002Fcompany\u002Fcm003-american-century-services-llc), where ML powers investment research and portfolio management. [Chicago](\u002Fjobs-in-chicago) serves as a hub for quantitative finance firms applying ML to market analysis and systematic trading. [Newport Beach](\u002Fjobs-in-newport-beach) hosts sophisticated investment managers like [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) that employ ML for fixed income markets and portfolio construction. The concentration of ML talent in these locations reflects the specialized nature of financial applications, where understanding market dynamics and financial products combines with technical expertise to create competitive advantages in the United States financial landscape.",{"title":26,"content":27},"In-Demand Skills & Employers","Leading American financial institutions seek professionals who combine Machine Learning with domain-specific expertise. Top employers like [CM003 American Century Services, LLC](\u002Fcompany\u002Fcm003-american-century-services-llc), [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance), and [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) require ML specialists with complementary skills in [Risk Management](\u002Fjobs-by-expertise\u002Frisk-management), [Portfolio Management](\u002Fjobs-by-expertise\u002Fportfolio-management), and [Financial Analysis](\u002Fjobs-by-expertise\u002Ffinancial-analysis). These companies value expertise in tools like FactSet and Bloomberg for market data integration, combined with ML applications for pattern recognition and alpha signal development. The most sought-after professionals understand both the technical aspects of ML and the financial context, including knowledge of IFRS standards, regulatory compliance, and financial markets. Experience with property & casualty insurance analysis, loss ratio modeling, and reinsurance knowledge is particularly valuable in the insurance sector, while investment firms prioritize skills in quantitative research, time-series analysis, and financial engineering. The integration of [Artificial Intelligence Tools](\u002Fjobs-by-skill\u002Fartificial-intelligence-tools) and natural language processing with traditional financial expertise creates the most compelling value proposition for employers across the United States.",{"title":29,"content":30},"Career & Development","Building a Machine Learning career in the United States financial sector requires a strategic combination of technical mastery and financial domain knowledge. Entry paths often begin with strong foundations in [Python](\u002Fjobs-by-skill\u002Fpython) programming, [SQL](\u002Fjobs-by-skill\u002Fsql) for data manipulation, and statistical analysis using R, progressing to advanced ML techniques and cloud platforms like AWS. Professionals should develop expertise in relevant financial domains such as [Financial Modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling), actuarial analysis, and investment strategy while mastering ML applications for specific use cases. Career advancement typically involves specialization in areas like algorithmic trading, risk modeling, or insurance analytics, with senior roles requiring leadership in ML implementation and strategy. Continuous learning through certifications in [Generative AI](\u002Fjobs-by-skill\u002Fgenerative-ai), Kubernetes for deployment, and financial regulatory frameworks ensures ongoing relevance. The most successful ML professionals in finance combine technical skills with deep understanding of market dynamics, financial products, and business objectives, creating solutions that drive tangible value for American financial institutions navigating increasingly complex and data-intensive environments.","expertise:machine-learning:us","2026-08-17T09:09:34.265401+02:00",{"total":34,"jobs":35},47,[36,96,131,158,194,228,281,326,359,395,428,469,498,520,557,581,606,629,654,678],{"id":37,"slug":38,"title":39,"raw_title":40,"is_featured":41,"company":42,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":45,"processed_country_iso_code_gmaps":47,"processed_home_office":49,"processed_salary_min":50,"processed_salary_max":51,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":54,"processed_employment_types":56,"processed_it_skills":57,"processed_it_skills_labels":60,"processed_job_expertise_skills":76,"processed_job_expertise_skills_labels":77,"max_cpc":94,"actual_cpc":95},88334,"principal-data-engineering-transamerica","Principal Data Engineering",null,false,{"name":43,"slug":44,"logo_url":40},"Transamerica","transamerica",[46],"Denver",[48],"US","onsite",120000,180000,"USD","estimated",[55],"FULL_TIME","permanent",{"etl":58,"sql":58,"java":59,"linux":59,"scala":59,"devops":59,"python":59,"node.js":59,"big data":58,"cloud computing":58,"shell scripting":59,"data warehousing":58,"data visualization tools":59,"real-time streaming analytics":58,"continuous integration\u002Fcontinuous delivery (ci\u002Fcd)":59},4,3,[61,62,63,64,65,66,67,68,69,70,71,72,73,74,75],"SQL","Linux","Shell Scripting","DevOps","Continuous Integration\u002FContinuous Delivery (CI\u002FCD)","Cloud Computing","Big Data","Real-time Streaming Analytics","Data Warehousing","ETL","Data Visualization Tools","Java","Python","Scala","Node.js",{"budgeting":59,"data lineage":58,"data quality":58,"data science":59,"data analytics":58,"data governance":58,"data engineering":58,"data integration":58,"machine learning":59,"data architecture":58,"delivery management":58,"metadata management":58,"strategy development":58,"business intelligence":58,"master data management":58,"database administration":58},[78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93],"Data Engineering","Data Architecture","Data Analytics","Business Intelligence","Database Administration","Data Integration","Data Science","Machine Learning","Data Governance","Master Data Management","Metadata Management","Data Quality","Data Lineage","Budgeting","Strategy Development","Delivery Management",1,1.5,{"id":97,"slug":98,"title":99,"raw_title":40,"is_featured":41,"company":100,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":103,"processed_country_iso_code_gmaps":105,"processed_home_office":106,"processed_salary_min":107,"processed_salary_max":108,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":109,"processed_employment_types":56,"processed_it_skills":110,"processed_it_skills_labels":112,"processed_job_expertise_skills":119,"processed_job_expertise_skills_labels":120,"max_cpc":94,"actual_cpc":95},84410,"quantitative-analyst-portfolio-engineering-analytics-invesco-advisors-inc","Quantitative Analyst, Portfolio Engineering & Analytics",{"name":101,"slug":102,"logo_url":40},"Invesco Advisors Inc.","invesco-advisors-inc",[104],"Boston",[48],"hybrid",130000,135000,[55],{"sql":59,"python":58,"pytorch":59,"tensorflow":59,"scikit-learn":59,"generative ai":111,"api development":59,"high performance computing":59},2,[73,61,113,114,115,116,117,118],"scikit-learn","TensorFlow","PyTorch","Generative AI","API development","High Performance Computing",{"statistics":58,"cfa progress":111,"optimization":58,"data management":59,"neural networks":59,"asset allocation":58,"machine learning":59,"financial engineering":58,"quantitative research":58,"portfolio construction":58,"risk models (barraone, axioma)":111},[121,122,123,124,125,85,126,127,128,129,130],"Financial Engineering","Statistics","Optimization","Portfolio Construction","Asset Allocation","Neural Networks","Risk Models (BarraOne, Axioma)","CFA Progress","Data Management","Quantitative Research",{"id":132,"slug":133,"title":134,"raw_title":40,"is_featured":41,"company":135,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":138,"processed_country_iso_code_gmaps":139,"processed_home_office":49,"processed_salary_min":140,"processed_salary_max":141,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":142,"processed_employment_types":40,"processed_it_skills":143,"processed_it_skills_labels":144,"processed_job_expertise_skills":146,"processed_job_expertise_skills_labels":147,"max_cpc":94,"actual_cpc":95},87373,"director-of-product-management-data-science-sedgwick-claims-management-services-inc","Director of Product Management, Data Science",{"name":136,"slug":137,"logo_url":40},"Sedgwick Claims Management Services Inc.","sedgwick-claims-management-services-inc",[],[48],150000,200000,[55],{"r":111,"sql":111,"python":111},[73,145,61],"R",{"forecasting":58,"data privacy":59,"data science":58,"data literacy":59,"machine learning":58,"model governance":58,"product management":58,"agile methodologies":58,"experimental design":59,"predictive modeling":58,"portfolio management":58,"statistical analysis":58},[148,84,149,150,151,152,153,154,155,156,85,157],"Product Management","Predictive Modeling","Statistical Analysis","Forecasting","Agile Methodologies","Model Governance","Data Privacy","Experimental Design","Portfolio Management","Data Literacy",{"id":159,"slug":160,"title":161,"raw_title":40,"is_featured":41,"company":162,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":165,"processed_country_iso_code_gmaps":167,"processed_home_office":106,"processed_salary_min":140,"processed_salary_max":141,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":168,"processed_employment_types":56,"processed_it_skills":169,"processed_it_skills_labels":170,"processed_job_expertise_skills":181,"processed_job_expertise_skills_labels":182,"max_cpc":94,"actual_cpc":95},83543,"application-engineering-manager-great-american-insurance-company","Application Engineering Manager",{"name":163,"slug":164,"logo_url":40},"Great American Insurance Company","great-american-insurance-company",[166],"Cincinnati",[48],[55],{"aws":59,".net":59,"java":59,"azure":59,"rally":59,"claude":59,"openai":59,"oracle":59,"python":59,"snowflake":59,"sql server":59,"github copilot":59,"api development":59},[73,72,171,172,173,174,175,176,177,178,179,180,117],".NET","SQL Server","Oracle","Snowflake","Azure","AWS","GitHub Copilot","Claude","OpenAI","Rally",{"sdlc":58,"cloud platforms":59,"machine learning":59,"budget management":59,"strategic planning":58,"process improvement":58,"software development":58,"ai-enabled development":59,"performance management":58,"application development":58,"requirements documentation":59,"agile methodologies (scrum, kanban, xp)":58},[183,184,185,85,186,187,188,189,190,191,192,193],"Software Development","Application Development","Agile Methodologies (Scrum, Kanban, XP)","SDLC","Strategic Planning","Process Improvement","Budget Management","Performance Management","Requirements Documentation","Cloud Platforms","AI-enabled Development",{"id":195,"slug":196,"title":197,"raw_title":40,"is_featured":41,"company":198,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":201,"processed_country_iso_code_gmaps":203,"processed_home_office":106,"processed_salary_min":204,"processed_salary_max":205,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":206,"processed_employment_types":56,"processed_it_skills":207,"processed_it_skills_labels":208,"processed_job_expertise_skills":221,"processed_job_expertise_skills_labels":222,"max_cpc":94,"actual_cpc":95},88425,"data-engineer-i-cloud-data-modernization-aws-databricks-dbt-sql-ai-travelers-indemnity-co","Data Engineer I - Cloud Data Modernization - AWS, Databricks, DBT, SQL, AI",{"name":199,"slug":200,"logo_url":40},"Travelers Indemnity Co","travelers-indemnity-co",[202],"Hartford",[48],109300,180200,[55],{"aws":58,"dbt":58,"sql":58,"pyspark":59,"ai tools":59,"databricks":58,"data quality":59,"data security":59,"data pipelines":58,"cloud platforms":58,"data governance":59,"data transformation":58,"programming languages":59,"software engineering practices":59},[176,209,210,61,211,212,213,214,215,216,217,218,219,220],"Databricks","dbt","PySpark","AI tools","Cloud platforms","Programming languages","Data pipelines","Data transformation","Data governance","Data security","Data quality","Software engineering practices",{"testing":59,"data analysis":58,"data modeling":58,"data management":59,"system analysis":59,"data engineering":58,"machine learning":59,"business intelligence":59,"artificial intelligence":59},[78,223,224,129,225,226,81,227,85],"Data Modeling","Data Analysis","System Analysis","Testing","Artificial Intelligence",{"id":229,"slug":230,"title":231,"raw_title":40,"is_featured":41,"company":232,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":233,"processed_country_iso_code_gmaps":234,"processed_home_office":106,"processed_salary_min":235,"processed_salary_max":236,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":237,"processed_employment_types":56,"processed_it_skills":238,"processed_it_skills_labels":239,"processed_job_expertise_skills":254,"processed_job_expertise_skills_labels":255,"max_cpc":94,"actual_cpc":95},88450,"lead-architect-ai-travelers-indemnity-co","Lead Architect (AI)",{"name":199,"slug":200,"logo_url":40},[202],[48],169400,279600,[55],{"aws":58,"gcp":59,"rag":58,"sql":59,"llms":58,"azure":59,"ci\u002Fcd":59,"mlops":58,"docker":59,"python":58,"pytorch":58,"agentic ai":58,"kubernetes":59,"tensorflow":58,"agent2agent":58,"openai codex":59,"generative ai":58,"github copilot":59,"vector databases":58,"multi-agent orchestration":58,"claude enterprise\u002Fcli\u002Fcode":59,"model context protocol (mcp)":58},[73,61,176,175,240,114,115,241,242,243,244,116,245,246,247,248,249,250,251,252,253,177],"GCP","Docker","Kubernetes","CI\u002FCD","MLOps","LLMs","RAG","Vector Databases","Agentic AI","Multi-agent Orchestration","Model Context Protocol (MCP)","Agent2Agent","Claude Enterprise\u002FCLI\u002FCode","OpenAI Codex",{"security":58,"ai ethics":58,"compliance":58,"resiliency":58,"statistics":58,"scalability":58,"ai governance":58,"deep learning":58,"system design":58,"linear algebra":58,"responsible ai":58,"value creation":58,"ai architecture":58,"bias mitigation":58,"business acumen":58,"neural networks":58,"interoperability":58,"machine learning":58,"cost optimization":58,"cloud architecture":58,"probability theory":58,"agile methodologies":58,"model risk management":58,"technology roadmapping":58,"enterprise architecture":58,"transformational change":58,"business capability models":58,"insurance industry knowledge":59,"regulatory frameworks (eu ai act, gdpr)":58},[256,85,257,126,258,122,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,152,277,278,279,280],"AI Architecture","Deep Learning","Linear Algebra","Probability Theory","AI Ethics","Bias Mitigation","Responsible AI","AI Governance","Model Risk Management","Regulatory Frameworks (EU AI Act, GDPR)","Insurance Industry Knowledge","Technology Roadmapping","Enterprise Architecture","Cloud Architecture","System Design","Scalability","Resiliency","Interoperability","Security","Compliance","Cost Optimization","Transformational Change","Business Acumen","Value Creation","Business Capability Models",{"id":282,"slug":283,"title":284,"raw_title":40,"is_featured":41,"company":285,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":288,"processed_country_iso_code_gmaps":290,"processed_home_office":106,"processed_salary_min":291,"processed_salary_max":292,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":293,"processed_employment_types":56,"processed_it_skills":294,"processed_it_skills_labels":295,"processed_job_expertise_skills":311,"processed_job_expertise_skills_labels":312,"max_cpc":94,"actual_cpc":95},83781,"senior-machine-learning-engineer-fraud-risk-modeling-government-employees-insurance-company","Senior Machine Learning Engineer, Fraud Risk Modeling",{"name":286,"slug":287,"logo_url":40},"Government Employees Insurance Company","government-employees-insurance-company",[289],"Palo 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