[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-expertise-machine-learning-us":3,"job-search-\u002Fde-us\u002Fjobs-by-expertise\u002Fmachine-learning?page=3":33,"expertise-filters-\u002Fde-us\u002Fjobs-by-expertise\u002Fmachine-learning?page=3":269,"featured-jobs-\u002Fde-us\u002Fjobs-by-expertise\u002Fmachine-learning?page=3":444},{"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,[36,108,138,180,206,233,256],{"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":86,"processed_job_expertise_skills_labels":87,"max_cpc":106,"actual_cpc":107},49186,"sr-database-engineer-amp-developer-security-data-mufg-bank-ltd","Sr. Database Engineer & Developer, Security Data",null,false,{"name":43,"slug":44,"logo_url":40},"MUFG Bank, Ltd.","mufg-bank-ltd",[46],"Jersey City",[48],"US","hybrid",140000,203000,"USD","estimated",[55],"FULL_TIME","permanent",{"sql":58,"java":59,"cribl":59,"kafka":59,"scala":59,"aws s3":59,"python":58,"splunk":59,"datadog":59,"elastic":59,"kinesis":59,"mongodb":59,"powerbi":59,"tableau":59,"bigquery":59,"dynamodb":59,"redshift":59,"snowflake":58,"databricks":59,"javascript":59,"postgresql":59,"cloud watch":59,"azure synapse":59,"aws cloudtrail":59,"azure event hub":59},4,3,[61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85],"SQL","Python","Snowflake","PowerBI","Tableau","Java","Scala","JavaScript","Splunk","Cribl","Elastic","Datadog","AWS CloudTrail","Cloud Watch","Azure Event Hub","AWS S3","Kafka","Kinesis","Databricks","BigQuery","Redshift","Azure Synapse","MongoDB","DynamoDB","PostgreSQL",{"ocsf":59,"otel":59,"compliance":59,"data privacy":59,"data modeling":58,"threat hunting":58,"data governance":58,"data engineering":58,"machine learning":59,"etl\u002Felt pipelines":58,"vendor management":59,"data normalization":58,"project management":59,"security frameworks":59,"detection engineering":58,"mitre attack framework":59,"security data analysis":58,"artificial intelligence":59},[88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105],"Data Engineering","Data Modeling","Data Normalization","ETL\u002FELT Pipelines","Data Governance","Security Data Analysis","Threat Hunting","Detection Engineering","Vendor Management","Project Management","Artificial Intelligence","Machine Learning","Data Privacy","Compliance","Security Frameworks","MITRE Attack Framework","OCSF","OTEL",1,1.5,{"id":109,"slug":110,"title":111,"raw_title":40,"is_featured":41,"company":112,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":115,"processed_country_iso_code_gmaps":116,"processed_home_office":117,"processed_salary_min":118,"processed_salary_max":119,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":120,"processed_employment_types":56,"processed_it_skills":121,"processed_it_skills_labels":123,"processed_job_expertise_skills":127,"processed_job_expertise_skills_labels":128,"max_cpc":106,"actual_cpc":107},64612,"ml-architect-sedgwick-claims-management-services-inc","ML Architect",{"name":113,"slug":114,"logo_url":40},"Sedgwick Claims Management Services Inc.","sedgwick-claims-management-services-inc",[],[48],"onsite",175000,220000,[55],{"r":58,"sql":58,"python":58,"microsoft office":122,"data visualization tools":59},2,[62,124,61,125,126],"R","Data Visualization Tools","Microsoft Office",{"data science":58,"etl pipelines":58,"data wrangling":58,"data exploration":58,"machine learning":58,"data visualization":59,"feature engineering":58,"predictive modeling":58,"statistical analysis":58,"natural language processing":59},[99,129,130,131,132,133,134,135,136,137],"Predictive Modeling","Data Science","Data Wrangling","Feature Engineering","Natural Language Processing","ETL Pipelines","Data Exploration","Statistical Analysis","Data Visualization",{"id":139,"slug":140,"title":141,"raw_title":40,"is_featured":41,"company":142,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":145,"processed_country_iso_code_gmaps":147,"processed_home_office":49,"processed_salary_min":148,"processed_salary_max":149,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":150,"processed_employment_types":56,"processed_it_skills":151,"processed_it_skills_labels":152,"processed_job_expertise_skills":165,"processed_job_expertise_skills_labels":166,"max_cpc":106,"actual_cpc":107},58526,"data-quality-engineer-merastar-insurance-company","Data Quality Engineer",{"name":143,"slug":144,"logo_url":40},"Merastar Insurance Company","merastar-insurance-company",[146],"Chicago",[48],99000,164800,[55],{"aws":59,"dbt":122,"git":122,"sql":58,"iics":58,"ci\u002Fcd":122,"kafka":122,"spark":122,"oracle":59,"python":58,"airflow":122,"power bi":59,"snowflake":58,"powershell":122,"informatica":58,"infrastructure as code":122},[61,153,154,63,62,155,156,157,158,159,160,161,77,162,163,164],"Informatica","IICS","Oracle","AWS","Power BI","Git","CI\u002FCD","PowerShell","Spark","Airflow","DBT","Infrastructure as Code",{"devops":122,"dataops":122,"compliance":59,"data testing":58,"data modeling":59,"data security":59,"data profiling":58,"data vault 2.0":122,"data governance":59,"data validation":58,"etl\u002Felt testing":58,"machine learning":122,"data reconciliation":58,"test data management":59,"data quality assurance":58,"ai-assisted development":122,"test environment strategy":59},[167,168,169,170,171,172,89,92,173,101,174,175,176,177,178,179,99],"Data Testing","Data Validation","Data Quality Assurance","ETL\u002FELT Testing","Data Reconciliation","Data Profiling","Data Security","Test Environment Strategy","Test Data Management","Data Vault 2.0","DataOps","DevOps","AI-assisted Development",{"id":181,"slug":182,"title":183,"raw_title":40,"is_featured":41,"company":184,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":187,"processed_country_iso_code_gmaps":189,"processed_home_office":117,"processed_salary_min":190,"processed_salary_max":191,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":192,"processed_employment_types":56,"processed_it_skills":193,"processed_it_skills_labels":194,"processed_job_expertise_skills":197,"processed_job_expertise_skills_labels":198,"max_cpc":106,"actual_cpc":107},53413,"principal-structured-crebpl-resi-desk-strat-apollo-management-holdings-lp","Principal, Structured CRE\u002FBPL Resi Desk Strat",{"name":185,"slug":186,"logo_url":40},"Apollo Management Holdings, L.P.","apollo-management-holdings-lp",[188],"Los Angeles",[48],300000,400000,[55],{"c#":59,"sql":59,"matlab":59,"python":58},[62,61,195,196],"MATLAB","C#",{"data analysis":58,"securitization":58,"risk assessment":58,"deal structuring":58,"machine learning":59,"cash flow modeling":58,"structured finance":58,"portfolio management":59,"artificial intelligence":59},[199,200,201,202,203,99,98,204,205],"Cash Flow Modeling","Structured Finance","Securitization","Risk Assessment","Deal Structuring","Portfolio Management","Data Analysis",{"id":207,"slug":208,"title":209,"raw_title":40,"is_featured":41,"company":210,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":213,"processed_country_iso_code_gmaps":215,"processed_home_office":49,"processed_salary_min":216,"processed_salary_max":217,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":218,"processed_employment_types":56,"processed_it_skills":219,"processed_it_skills_labels":220,"processed_job_expertise_skills":224,"processed_job_expertise_skills_labels":225,"max_cpc":106,"actual_cpc":107},68780,"experienced-data-scientist-auto-owners-insurance-company","Experienced Data Scientist",{"name":211,"slug":212,"logo_url":40},"Auto-Owners Insurance Company","auto-owners-insurance-company",[214],"Lansing",[48],120000,160000,[55],{"r":59,"aws":122,"sql":58,"keras":59,"python":59,"tensorflow":59,"scikit-learn":59},[61,124,62,221,222,223,156],"TensorFlow","Scikit-learn","Keras",{"data analysis":58,"cloud computing":122,"machine learning":58,"feature engineering":58,"statistical modeling":58,"model lifecycle management":58,"insurance industry knowledge":122},[226,227,228,229,230,231,232],"Statistical modeling","Machine learning","Data analysis","Model lifecycle management","Feature engineering","Cloud computing","Insurance industry knowledge",{"id":234,"slug":235,"title":236,"raw_title":40,"is_featured":41,"company":237,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":240,"processed_country_iso_code_gmaps":242,"processed_home_office":117,"processed_salary_min":243,"processed_salary_max":244,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":245,"processed_employment_types":56,"processed_it_skills":246,"processed_it_skills_labels":247,"processed_job_expertise_skills":250,"processed_job_expertise_skills_labels":251,"max_cpc":106,"actual_cpc":107},65332,"senior-aiml-engineer-starr-insurance-holdings-inc","Senior AI\u002FML Engineer",{"name":238,"slug":239,"logo_url":40},"Starr Insurance Holdings, Inc.","starr-insurance-holdings-inc",[241],"New York",[48],180000,200000,[55],{"aws":59,"sql":59,"azure":59,"python":58,"big data solutions":59},[62,61,248,156,249],"Azure","Big Data Solutions",{"statistics":58,"data mining":58,"deep learning":58,"machine learning":58,"actuarial science":122,"predictive modeling":58,"natural language processing":59},[99,252,253,254,129,133,255],"Deep Learning","Statistics","Data Mining","Actuarial Science",{"id":257,"slug":258,"title":259,"raw_title":40,"is_featured":41,"company":260,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":261,"processed_country_iso_code_gmaps":262,"processed_home_office":117,"processed_salary_min":263,"processed_salary_max":118,"processed_salary_currency":52,"processed_salary_source":53,"processed_working_hours":264,"processed_employment_types":56,"processed_it_skills":265,"processed_it_skills_labels":266,"processed_job_expertise_skills":267,"processed_job_expertise_skills_labels":268,"max_cpc":106,"actual_cpc":107},65298,"aiml-engineer-starr-insurance-holdings-inc","AI\u002FML Engineer",{"name":238,"slug":239,"logo_url":40},[241],[48],135000,[55],{"r":58,"python":58},[62,124],{"data mining":58,"deep learning":58,"data wrangling":58,"machine learning":58,"actuarial science":122,"predictive modeling":58,"statistical analysis":58},[99,252,129,254,136,131,255],{"industry":270,"employment_type":301,"expertise_skills":308,"it_skills":373,"salary_currency":440,"processed_working_hours":442},[271,275,279,283,286,289,292,295,298],{"key":272,"label":273,"count":274},"insurance","Insurance",27,{"key":276,"label":277,"count":278},"financial services","Financial Services",12,{"key":280,"label":281,"count":282},"banking","Banking",8,{"key":284,"label":285,"count":122},"asset management","Asset Management",{"key":287,"label":288,"count":122},"risk management","Risk Management",{"key":290,"label":291,"count":106},"financial regulation","Financial Regulation",{"key":293,"label":294,"count":106},"claims administration","Claims Administration",{"key":296,"label":297,"count":106},"alternative asset management","Alternative Asset Management",{"key":299,"label":300,"count":106},"credit union","Credit 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