Fully Remote Role : Data Scientist

Position Overview

As a Data Scientist, you will work closely with stakeholders across Actuarial, Underwriting, Claims, Product, Revenue, and Customer Experience. Your primary role involves developing predictive models, testing hypotheses, exploring new data sources, and integrating these findings into business workflows and internal data infrastructure.

What You'll Do

• Cross-Functional Partnership: Partner with teams across the business to translate their goals into analytical approaches and communicate actionable findings.
• Behavioral Analysis: Analyze customer and broker behavior to improve engagement, retention, and conversion through segmentation, churn analysis, and anomaly detection.
• Hypothesis Testing: Investigate business problems and test hypotheses using rigorous data exploration, such as evaluating risk factors for high loss ratios or finding operational efficiencies.
• Predictive Modeling: Build statistical and machine learning models (e.g., regression, classification, clustering) to support pricing, reserving, underwriting, and claims initiatives.
• Data Exploration: Evaluate and incorporate new internal and third-party datasets into models and dashboards to boost performance and unlock insights.
• Operationalization: Integrate models into departmental workflows and tools by collaborating with engineering and product teams to ensure reliability and scalability.
• Infrastructure Improvement: Enhance internal data infrastructure by maintaining ETLs, developing APIs, and optimizing the reporting and dashboarding ecosystem.
• Ad-Hoc Support: Provide quick answers to pressing questions through deep dives and identify long-term opportunities for automation.

What We're Looking For

• 5+ years of experience in a data science, analytics, or statistics-focused role.
• Excitement for collaborating with business leads across various functions to solve real, day-to-day problems with data.
• Hands-on experience with predictive modeling, including regression, classification, clustering, and other machine learning techniques.
• Proficiency in Python and SQL.
• Bonus: Familiarity with advanced statistical modeling (e.g., Bayesian or hierarchical models) and P&C insurance data.