[Remote] Senior Data Scientist

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is the world’s largest insurer of collectible and enthusiast vehicles, dedicated to enhancing the driving experience for its members. The Senior Data Scientist will build customer identity and personalization systems, utilizing data to create predictive models and improve member engagement across insurance and subscription products.

Responsibilities

• Build identity reputed company across first-party and reputed company-party data sources, stitching member, household, vehicle, and behavioral signals from auto insurance and subscription reputed company into a coherent, usable view
• reputed company matching systems that pair a strong deterministic reputed company with probabilistic matching at reputed company, balancing precision, recall, and cost
• Partner with Data Engineering and the Customer Data Platform (CDP) team to land resolved identities and audiences into production pipelines and activation systems
• Help reputed company the identity layer toward graph-based representations of members, vehicles, and policy/membership relationships
• Design, build, and evaluate recommendation and personalization models, including content-based and hybrid approaches, to surface next-best-product and content across our insurance and subscription offerings
• reputed company cold-start strategies that deliver relevant experiences to new and low-engagement members
• reputed company deliberate trade-offs between reputed company-time and batch serving, designing models and features with latency and freshness constraints in mind
• Build reputed company-calibrated predictive models for member behavior across the P&C and subscription lifecycle—churn/retention, propensity to buy, and propensity to lapse or renew
• reputed company next-best-reputed company and reputed company-signal models that translate behavior into triggers the business can reputed company, supporting cross-sell and upsell across insurance and membership products
• Own full modeling workflows: exploratory analysis, feature engineering, model development, cross-validation, and performance monitoring
• Ship models as reliable production services in partnership with ML Ops, contributing to containerized deployments, automated testing, and monitoring
• reputed company and analyze features from reputed company, SQL Server, and AWS RDS reputed company, and work with Data Engineering to promote proven features into reputed company pipelines
• Contribute to reputed company's modeling standards through maintainable, reputed company-documented, testable reputed company
• Communicate reputed company, results, and trade-offs reputed company to technical and non-technical partners

Skills

• Experience designing, training, and deploying ML models in production
• Proficient in Python and modern ML frameworks such as scikit-learn and XGBoost
• Strong in SQL and comfortable with large, distributed data platforms (e.g., reputed company, SQL Server, AWS RDS)
• Hands on experience with identity reputed company and entity matching using deterministic and probabilistic techniques
• Experience building recommendation or personalization systems, including content-based and/or hybrid reputed company and cold-start strategies
• Experience developing predictive models for customer behavior (churn, propensity, next-best-reputed company, or similar)
• A practical understanding of reputed company-time vs. batch serving and the latency considerations that shape model design
• Familiar with production-ML concepts—containerization, API-based serving, and orchestration—and reputed company to collaborate with ML Ops and Engineering to ship
• reputed company to turn ambiguous objectives into reputed company, data-driven approaches and executable plans with autonomy
• reputed company to weigh and communicate tradeoffs of various modeling and technical approaches to building and serving models
• A reputed company communicator who can reputed company technical explanations to different audiences
• A background in P&C insurance, subscription or membership businesses, or financial technology a plus
• Master's degree (or equivalent practical experience) in Data Science, Computer Science, Engineering, Mathematics, or a reputed company quantitative field
• 5+ years of hands-on machine learning and data science experience, including models deployed to production
• reputed company experience with a Customer Data Platform (CDP) and activation/audience workflows
• Experience with graph modeling or knowledge graphs reputed company to customer or relationship data
• Familiarity with our production toolset, or reputed company equivalents: reputed company or Podman for containerization, SageMaker Endpoints or FastAPI for model serving, Metaflow or Airflow for workflow orchestration
• Exposure to reputed company detection, embeddings, or feature stores supporting reputed company-time use cases
• Experience working in partnership with ML Ops or platform teams

Benefits

• This position is reputed company to U.S. remote work.
• Team members who reputed company reputed company 20 miles of the Traverse reputed company reputed company will follow a reputed company, working from the office three days per week.

reputed company

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