Data Scientist (Insurance Product)-Senior Associate

JPMorgan Chase & Co.•Columbus, OH

1d•$95,000 - $145,000

About The Position

Are you passionate about applying data science and AI to build new products and shape client experiences at scale? If you enjoy solving complex business problems analytically, using AI in your day-to-day workflow, and influencing strategy for a growing line of business, then this opportunity is for you. As a Data Scientist for Insurance Products on our Small Business Data and Analytics team, you'll have the opportunity to be at the forefront of building a best-in-class, integrated, digital-led P&C (Property & Casualty) Insurance business within a leading financial services brand, focused on deepening relationships with our more than 7 million small business clients. You'll need to partner cross-functionally to establish product analytics foundations, develop scalable lead- and trigger-driven capabilities, and support testing and experimentation to improve measurable outcomes. You will incorporate AI-native thinking, including practical application of AI in everyday analysis, decision support, and innovation, as well as a strong curiosity to identify, prototype, and scale new agentic use cases that improve product and client outcomes. You'll need to be an avid learner with a growth mindset that's eager to apply data science and AI to help launch and evolve one of the most significant growth opportunities in Business Banking.

Requirements

Bachelor’s degree in quantitative field (Computer Science, Engineering, Operations Research, Statistics, Economics, or related discipline) and 3 years of experience in advanced analytics roles
Strong proficiency in statistical analysis, hypothesis testing, predictive modeling, and experimental design for product and customer use cases
Talented in data querying, transformation, and analysis using modern analytical tools and programming languages (Python and SQL)
Demonstrated AI fluency, including ability to use AI tools effectively in day-to-day analytical work to accelerate insight generation and improve solution quality
Competent leveraging data visualization tools such as Tableau
Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations
Strong data storytelling capabilities, including communicating complex concepts to audiences of varying levels across business and technical functions
Demonstrated ability to work in cross-functional environments, align stakeholders, and deliver high-quality outputs in a dynamic product setting
Strong commitment to iterative development and measurable outcomes, with the ability to incorporate feedback and continuously improve analytical and AI-enabled solutions
Demonstrated learning agility and curiosity to stay current on AI advances and apply them responsibly in a regulated environment

Nice To Haves

Insurance industry/product knowledge highly desired
Experience supporting product analytics, product launch measurement, and experimentation in client-facing businesses
Experience presenting analytical insights and recommendations to senior leaders and cross-functional decision-makers
Familiarity with analytics approaches for customer journey optimization, lead management, and performance measurement frameworks
Experience developing, testing, or scaling AI-enabled and agentic use cases in business workflows
Experience partnering with product and technology teams to translate AI opportunities into practical, measurable outcomes

Responsibilities

Collaborate with product, strategy, risk, controls, operations, and customer teams to provide analytical support for Small Business Insurance initiatives and decision-making
Apply statistical methods, data analysis, and AI-assisted approaches to solve business problems related to product performance, client engagement, and growth outcomes
Support end-to-end analytics delivery, from problem framing and measurement design through insight generation and communication to senior stakeholders
Develop and refine analytics approaches for lead and trigger capabilities that help improve demand generation and client traffic in a scalable, sustainable manner
Partner cross-functionally to set up day-one measurements, including tracking, data quality, and KPI frameworks across financial, operational, controls, audit, and product dimensions.
Operationalize experimentation frameworks to evaluate product and journey enhancements, quantify impact, and inform prioritization.
Analyze client experience and journey outcomes, including AI-enabled discovery and servicing pathways, to identify opportunities for improvement and measurable value creation
Identify and develop high-value AI and agentic use cases that can improve analytical productivity, decision quality, and client outcomes