We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
Position Overview
The Data Scientist is responsible for building and deploying analytical and machine learning solutions that address complex business and regulatory needs. The role works closely partners across Product, Underwriting, and Risk to deliver scalable, secure, and production-ready solutions.
Successful candidates combine solid statistical modeling and ML fundamentals, strong Python skills, and a growing ability to communicate analytical outcomes to business partners. This role is well-suited for someone who brings intellectual curiosity, a bias toward action, and a collaborative mindset, and who is looking to deepen their modeling expertise while taking on increasing responsibility over time.
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Key Responsibilities
- Modeling & Evaluation: Build and evaluate models using GLMs, GBMs, and related approaches. Assess model performance and stability, diagnose overfitting, and document findings clearly for technical and non-technical audiences.
- Third-Party Data & Vendor Support: Assist in managing third-party data relationships, including data intake, validation, and iterative testing. Engage with external vendors to resolve discrepancies and ensure data quality.
- Business Partnership & Communication: Collaborate with business stakeholders to understand analytical objectives and contribute to translating results into clear recommendations. Develop comfort presenting findings and explaining tradeoffs to partners with varying levels of technical fluency.
- Analytical Execution: Contribute to process improvement and automation efforts to reduce manual effort and increase analytical throughput. Support work across multiple lines of coverage with attention to rigor and consistency.
- Monitoring & Governance: Help define and track metrics for classification, forecasting, and business KPIs. Support A/B testing, monitor for drift, and contribute to compliance, privacy, and responsible modeling standards.
- Continuous Learning: Stay current on developments in ML, statistical modeling, and best practices. Build familiarity with the broader analytical toolkit and contribute to reusable templates and documentation.
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Required Skills & Experience
Experience Range - 4 to 6 Years
