Sobre este puesto de Senior Data Scientist en Hagerty
Say hello to Hagerty
Hagerty is a company built by drivers for drivers. We put our members at the center of everything we do and are dedicated to making it easier and more enjoyable for enthusiasts to drive and celebrate the machines they love. We’re proud to be the world’s largest insurer of collectible and enthusiast vehicles and are home to the Hagerty Drivers Club, the world’s largest car club. Our Marketplace business presents live and digital sales across the U.S. and Europe, we host a number of driving events and concours, and our award-winning automotive journalists produce the most popular car magazine globally, alongside internationally awarded videos. We’re committed to Never Stop Driving. Ready to get in the driver’s seat? Join us!
As a Senior Data Scientist at Hagerty, you'll build the customer identity and personalization layer that powers how we understand and engage members across our subscription and property & casualty (P&C) insurance products. This is a hands-on, build-and-ship role on the Data Science team, working in close partnership with ML Ops, Data Engineering, and Marketing/Product.
You'll help create a unified, resolved view of each member across our data ecosystem—spanning auto insurance policies, subscription memberships, and the broader automotive enthusiast community—and turn it into recommendation, personalization, and predictive models that deliver the right message at the right moment. The goal is a system where identity, relevance, and timing work together to make every member interaction feel personal—at scale.
What you’ll do
Customer Identity & Data Foundations
- Build identity resolution across first-party and third-party data sources, stitching member, household, vehicle, and behavioral signals from auto insurance and subscription touchpoints into a coherent, usable view.
- Develop matching systems that pair a strong deterministic foundation with probabilistic matching at scale, 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 evolve the identity layer toward graph-based representations of members, vehicles, and policy/membership relationships.
Recommendation & Personalization
- 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.
- Develop cold-start strategies that deliver relevant experiences to new and low-engagement members.
- Make deliberate trade-offs between real-time and batch serving, designing models and features with latency and freshness constraints in mind.
Predictive Modeling
- Build well-calibrated predictive models for member behavior across the P&C and subscription lifecycle—churn/retention, propensity to buy, and propensity to lapse or renew.
- Develop next-best-action and journey-signal models that translate behavior into triggers the business can act on, 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.
Productionization & Collaboration
- Ship models as reliable production services in partnership with ML Ops, contributing to containerized deployments, automated testing, and monitoring.
- Source and analyze features from Snowflake, SQL Server, and AWS RDS Postgres, and work with Data Engineering to promote proven features into scalable pipelines.
- Contribute to the team's modeling standards through maintainable, well-documented, testable code.
- Communicate methods, results, and trade-offs clearly to technical and non-technical partners.
This Might Describe You
- 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., Snowflake, SQL Server, AWS RDS).
- Hands on experience with identity resolution and entity matching using deterministic and probabilistic techniques.
- Experience building recommendation or personalization systems, including content-based and/or hybrid methods and cold-start strategies.
- Experience developing predictive models for customer behavior (churn, propensity, next-best-action, or similar).
- A practical understanding of real-time vs. batch serving and the latency considerations that shape model design.
- Familiar with production-ML concepts—containerization, API-based serving, and orchestration—and able to collaborate with ML Ops and Engineering to ship.
- Able to turn ambiguous objectives into clear, data-driven approaches and executable plans with autonomy
- Able to weigh and communicate tradeoffs of various modeling and technical approaches to building and serving models
- A clear communicator who can tailor technical explanations to different audiences.
- A background in P&C insurance, subscription or membership businesses, or financial technology a plus.
Preferred
- Master's degree (or equivalent practical experience) in Data Science, Computer Science, Engineering, Mathematics, or a related quantitative field.
- 5+ years of hands-on machine learning and data science experience, including models deployed to production.
- Direct experience with a Customer Data Platform (CDP) and activation/audience workflows.
- Experience with graph modeling or knowledge graphs applied to customer or relationship data.
- Familiarity with our production toolset, or close equivalents:
- Docker or Podman for containerization
- SageMaker Endpoints or FastAPI for model serving
- Metaflow or Airflow for workflow orchestration
- Exposure to anomaly detection, embeddings, or feature stores supporting real-time use cases.
- Experience working in partnership with ML Ops or platform teams.
Other things to note
- This position is open to U.S. remote work. However, team members who reside within 20 miles of the Traverse City headquarters will follow a hybrid schedule, working from the office three days per week.
- May require travel for quarterly events.
- Familiarity with public company requirements, including Sarbanes Oxley and key regulations, if applicable. For SOX compliant roles, responsible for designing, executing, and documenting internal controls where they have been identified as owners to prevent errors in financial reporting, processes, and business operations. Including attestation to the completeness, accuracy, and compliance of all financial reporting data, where applicable.
If you reside in the following jurisdictions: Illinois, Colorado, California, District of Columbia, Hawaii, Maryland, Minnesota, Nevada, New York, or Jersey City, New Jersey, Cincinnati or Toledo, Ohio, Rhode Island, Washington, British Columbia, Canada please email [email protected] for compensation, comprehensive benefits and the perks that set us apart.
At Hagerty, we share the road. We are an inclusive automotive community where all are welcomed, valued and belong regardless of race, gender, age, or car preference. We are united by our shared passion for driving, our commitment to preserve car culture for future generations and our desire to make a positive impact in the world.
#LI-Remote / #LI-Hybrid / #LI-Onsite
EEO/AA
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
