The Global Retail Markets PDM Demand Modeling team is seeking an independent, creative, and self-motivated individual contributor to work on US Personal Lines.  The Demand Modeling Team builds complex demand models for customer retention, conversion, price elasticity, lifetime value, and cost-benefit analyses for all GRM lines of business. The analyst will contribute to model development and implementation, with a focus on incorporating Lifetime Value (LTV) into pricing. The analyst will also contribute to the development and enhancement of demand-based calibration tools to support new rating program rollouts.

More generally, we collaborate with business partners to develop predictive analytic solutions that enable data-driven strategic decision-making. The analyst in this role will utilize data science techniques to manipulate large structured and unstructured data sets, identify patterns in raw data, and develop models to predict the likelihood of a future outcome and/or to optimize business solutions. This level reflects solid knowledge of predictive analytics techniques, and proficiency in applying techniques to solve business issues.

Responsibilities:

• Build complex retention, conversion, and price elasticity models across GRM with a focus on Personal Lines using various techniques including GLMs and machine learning.
• Generate data-driven answers to open-ended strategic questions related to customer demand (e.g., price presentation, adverse selection, underwriting strategy).
• Mines large data sets using sophisticated analytical techniques to generate insights and inform business decisions.
• Responsible for large, sophisticated components of highly complex projects.
• Guides aspects of project design as a technical consultant for the team.
• Enables the business to evaluate trade-offs between and among choices, with a reasonable view into likely outcomes.
• Drives innovation in the application and development of tools and practices.
• Identifies and tests hypotheses, ensuring statistical significance, and builds predictive models for business application.
• Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
• Customizes analytic solutions to specific client needs.
• Regularly engages with the data science community and leads cross functional working groups.
• Potential for up to 10% travel
• The actual internal level/grade for this role will depend on the candidate’s overall experience and skill level

Job Specifications:

Reference: 2022-48252
Category: Data Science
Primary Location: Remote
Additional Locations:
Schedule: Full-Time

Salary: USD-$113,400.00-–-$184,100.00-/-Year
Education Level:
Travel: As Needed