What are the responsibilities and job description for the Data and Analytics - Business Insurance Data Science Executive Director position at JPMorgan Chase?
Join the team that will build and lead a high-performing team of analytics leaders, data scientists, and analysts to shape the strategic direction of JPMorgan Chase insurance agency business ensuring AI is not an afterthought but the foundation upon which the business is built.
As a Business Insurance Data Science Executive Director, within Data and Analytics Team, you will define the analytics and AI vision for a business being built from zero to one and partner closely with Insurance, Product, Distribution, and Technology leaders to architect AI-native capabilities that inform how we enter markets, design products, acquire and serve customers, and grow agency relationships.
Job Responsibilities:
- Define and execute the end-to-end analytics and AI strategy for the Business Insurance division, establishing the foundational data infrastructure, team structure, and analytical roadmap from inception with an AI-first orientation and architect AI-native solutions across the insurance value chain—ensuring that market entry strategy, agency distribution, product development, pricing, customer acquisition, and retention are powered by intelligent, data-driven systems from the outset.
- Partner with Insurance, Product, Marketing, and Technology leaders to translate business questions into analytical and AI-driven frameworks, delivering insights and automated capabilities that directly inform GTM decisions, product launches, and growth strategies.
- Design and deploy AI and machine learning models that support agency performance management, customer segmentation, cross-sell and upsell optimization, lifetime value estimation, and real-time decisioning.
- Identify and implement generative AI, agentic AI, and automation opportunities across the business—including intelligent document processing, conversational interfaces, content generation, and AI-assisted workflows for agents and customers.
- Design and implement measurement frameworks and experimentation programs (A/B testing, causal inference) to evaluate product-market fit, marketing effectiveness, and AI model performance.
- Develop competitive intelligence capabilities, leveraging internal and external data to benchmark performance, identify market white space, and inform strategic planning.
- Lead analytics and AI for customer experience, identifying friction points, optimizing digital and agent-assisted journeys through intelligent personalization, and delivering actionable recommendations to improve satisfaction and conversion.
Required Qualifications, Capabilities, and Skills:
- Master's or PhD in a quantitative field; 10 years of analytics and AI experience
- Experience building and scaling analytics/AI teams from the ground up, including managing managers
- Deep expertise in machine learning, predictive modeling, experimentation, and statistical inference
- Track record of translating AI capabilities into measurable business outcomes
- Strong executive communication skills and ability to influence senior leadership
- Experience operating across product, marketing, distribution, and finance functions simultaneously
- Proficiency in Python and/or R, SQL, and cloud-based platforms (Snowflake, Databricks, or equivalent)
Preferred Qualifications, Capabilities, and Skills:
- Insurance, insurtech, or adjacent industry experience (lending, payments, wealth management) and building a business or function from zero to one in a greenfield environment
- Hands-on experience deploying generative AI, LLMs, RAG, or agentic AI into production and designing AI-first operating models and embedding AI into core business processes
- Knowledge of responsible AI, model governance, and insurance regulatory considerations and impacting AI adoption through change management and organizational enablement
- Familiarity with Agile delivery and modern product development practices