Data Scientist, Tech Lead

📋 Description

• • Own the full lifecycle of high-impact machine-learning and generative-AI products that touch every corner of Hagerty—from predicting insurance risk to powering personalized marketplace recommendations and AI-driven membership experiences.
• • Architect, prototype, and productionize supervised models, anomaly-detection systems, graph-based algorithms, and LLM-driven agents that process petabytes of automotive, telematics, auction, and behavioral data.
• • Lead technical design sessions, translate ambiguous business questions into crisp data-science problem statements, and deliver end-to-end solutions with measurable ROI for insurance underwriting, dynamic pricing, fraud detection, marketing attribution, and customer-lifecycle optimization.
• • Write elegant, scalable Python code leveraging scikit-learn, XGBoost, PyTorch, NetworkX, and cutting-edge GenAI libraries; build containerized micro-services (FastAPI, Docker/Podman) orchestrated through Metaflow and Airflow that deploy seamlessly on AWS and on-prem clusters.
• • Establish rigorous MLOps practices—CI/CD pipelines, feature stores, model registry, automated retraining, drift detection, and governance dashboards—ensuring every model is reproducible, explainable, and compliant with SOX and other regulatory frameworks.
• • Query and engineer data from Snowflake, SQL Server, and RDS Postgres; design dimensional models, feature pipelines, and real-time streaming jobs that guarantee data quality, lineage, and privacy-by-design.
• • Serve as the go-to technical mentor: conduct deep-dive code reviews, pair program on complex algorithms, and upskill junior data scientists on advanced techniques such as retrieval-augmented generation, fine-tuning LLMs, graph neural networks, and Bayesian optimization.
• • Influence the strategic roadmap by evaluating emerging research, championing new tooling (e.g., LangChain, vector databases, causal-inference frameworks), and building proof-of-concepts that secure executive buy-in and budget.
• • Collaborate daily with engineering, MLOps, DevOps, product managers, actuaries, marketers, and insurance leaders; distill sophisticated model outputs into clear narratives, dashboards, and C-suite briefings that drive data-driven decisions across the enterprise.
• • Monitor post-deployment performance, design A/B and multivariate tests, and rapidly iterate to improve accuracy, fairness, and business impact while maintaining 99.9 % uptime for mission-critical services.
• • Drive cross-functional alignment during quarterly planning, estimate effort and risk, and shepherd projects from ideation through go-live, ensuring transparent milestones and stakeholder satisfaction.
• • Contribute to Hagerty’s culture of innovation by hosting internal tech talks, publishing blog posts, and participating in automotive-data conferences that showcase our thought leadership in AI for mobility and specialty insurance.
• • Uphold the highest standards of data ethics, privacy, and security, embedding responsible-AI principles into every experiment and product release.