Quant Analytics Executive Director - Card Data Analytics

JPMorgan Chase & Co.•New York, NY

21h•$190,000 - $285,000

About The Position

You can shape how customers experience lending—from what they see and qualify for, to how they manage repayment and stay on track over time. You will lead a high-impact analytics function that connects customer journeys, product strategy, and risk-adjusted economics. Join us to build scalable, data-driven decisioning that improves both customer outcomes and portfolio performance. As an Executive Director — Lending & Installment Analytics at JPMorganChase within Lending and Installment Analytics, you will lead enterprise analytics that informs what to offer, to whom, when, and through which experience. You will partner across Product, Marketing, Risk, Finance, and Operations to drive clear priorities, measurable results, and responsible use of advanced analytics. You will bring strong leadership and storytelling to influence decisions, align stakeholders, and scale impact.

Requirements

8+ years of experience in analytics, data science, or quantitative strategy roles within lending, credit, or consumer financial products
5+ years of experience leading and developing high-performing analytics teams, including people leadership and talent development
Demonstrated experience driving portfolio growth and credit performance using data-driven decisioning across the customer lifecycle
Demonstrated ability to translate customer journey insights into product strategy and prioritized roadmaps with measurable outcomes
Demonstrated experience with experimentation design and causal measurement, including hypothesis development, test design, and evaluation
Demonstrated experience building and using product economics models (for example, contribution margin, cohort economics, lifetime value, and loss forecasting) to support investment decisions
Demonstrated experience partnering cross-functionally with Product, Marketing, Risk, Finance, and Operations to deliver shared outcomes
Strong executive communication skills, including structured tradeoffs, clear recommendations, and crisp storytelling grounded in data
Working knowledge of model governance, monitoring, and responsible use expectations for analytics in regulated environments

Nice To Haves

Experience building “next best action” and personalization decisioning across multiple channels and servicing touchpoints
Experience with real-time decisioning systems, optimization approaches, and measurement frameworks for incremental impact
Experience modernizing analytics reporting and enabling self-service insights through standardized metrics and dashboards
Advanced degree in a quantitative field (for example, statistics, economics, computer science, engineering, or mathematics)

Responsibilities

Lead the Lending and Installment Analytics team to deliver insights and decisioning that optimize portfolio growth, customer value, and credit performance across installment and revolving lending
Build orchestration frameworks that unify channel, product, and lifecycle decisioning to enable consistent “next best action” and “next best product” recommendations across key touchpoints
Translate customer journey insights into product strategy by mapping end-to-end journeys (origination through retention) and identifying friction, drop-offs, and value moments
Partner with Product, Marketing, Risk, Finance, and Operations to set a shared analytics vision and deliver against strategic priorities across growth, engagement, losses, economics, and customer experience
Drive product economics and financial modeling, including contribution margin, cohort economics, lifetime value, loss forecasting, and sensitivity analysis to inform investment decisions
Define modeling strategy and guide teams building propensity, uplift, eligibility, and lifecycle behavior models with strong validation, monitoring, and governance
Guide lifecycle targeting and decisioning (pre-origination through servicing) across approval and eligibility, line assignment, pricing, term selection, and retention strategies
Scale experimentation in partnership with a testing center of excellence by defining hypotheses, test design, success metrics, and causal measurement approaches
Establish best-in-class measurement approaches (attribution and incrementality) appropriate for lending contexts to separate true lift from correlation
Build robust reporting and governance by defining objectives and key results (OKRs), standardizing metric definitions, enabling self-serve dashboards, and running recurring business reviews
Operationalize insights through decision engines, real-time personalization, and optimization while ensuring responsible use and strong model risk management practices