Hagerty is looking to solve machine learning and generative AI initiatives across the entire company, including insurance, online marketplaces, membership, and marketing, by hiring a Data Scientist, Tech Lead to operate as a technical leader on the Data Science team.
Requirements
- Strong proficiency with Python and ML frameworks such as scikit-learn, XGBoost, and PyTorch.
- Deep experience with SQL and data modeling in Snowflake, SQL Server, or similar distributed environments.
- Hands-on experience building containerized applications and deploying using FastAPI, Docker/Podman, and workflow orchestration tools like Metaflow or Airflow.
- Experience with generative AI (LLMs, embeddings, agents, RAG, fine-tuning) in a production or near-production context.
- Experience with graph modeling, anomaly detection systems, or agent-based approaches.
- Familiarity with automotive, insurance, or marketplace data.
- Experience in environments where data scientists own both modeling and MLOps responsibilities (~50/50 split)
Responsibilities
- Plan, design, develop, and deploy end-to-end predictive, prescriptive, and generative models—including supervised ML, anomaly detection, agentic systems, and graph-based models.
- Build production-ready ML and GenAI applications using Python, scikit-learn, XGBoost, PyTorch, NetworkX, and related tools.
- Develop and evaluate LLM-driven applications, retrieval systems, embeddings, fine-tuning strategies, and agent workflows.
- Own the full lifecycle of model deployment using Metaflow, Airflow, containerization (Podman/Docker), FastAPI, and related tooling.
- Collaborate with MLOps and DevOps teams to design scalable workflows, CI/CD pipelines, monitoring systems, and model governance processes.
- Monitor, evaluate, and remediate model performance in production environments.
- Write high-quality code to query, transform, and analyze large datasets from Snowflake, SQL Server, and AWS RDS Postgres.
Other
- Master’s degree or higher degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (or equivalent practical experience).
- Strong communication skills with an ability to simplify complex technical ideas for executives and business stakeholders.
- Proven track record of mentoring other data scientists and delivering high-quality technical reviews.
- May require travel for quarterly events.
- Familiarity with public company requirements, including Sarbanes Oxley and key regulations, if applicable.
