Quant Analytics Card Finance Senior Associate

JPMorgan Chase & Co.•Wilmington, DE

About The Position

Join our Credit Strategy Forecasting & Model Governance team within Consumer and Business Banking for an exciting opportunity to develop, maintain, and govern quantitative forecasting frameworks that estimate customer credit behavior and engagement over multiple years horizons. As a Senior Associate on the Card Finance Analytics team, you will serve as a key liaison between Risk, Finance, and Analytics teams, ensuring that forecasting models are methodologically sound, well-documented, and compliant with internal governance standards. As a high-visibility role, you will have direct impact on how the business evaluates the profitability and risk of credit line management strategies. Your outputs will directly inform financial planning, investment decisions, and risk management strategies across the credit card portfolio.

Requirements

Bachelor's or Master's degree in Statistics, Mathematics, Economics, Finance, Engineering, or a related quantitative field.
4+ years of experience in credit risk analytics, multi-year financial forecasting, or model development
Proficiency in Microsoft Excel for financial modeling and output presentation
Strong proficiency in statistical and financial modeling, including time-series analysis, segmentation, and extrapolation techniques.
Hands-on experience with SAS and/or SQL for extracting, transforming, and summarizing large datasets from enterprise data warehouses.
Solid understanding of outstanding balances, revolving behavior, sales activity, and NPV and P&L frameworks.
Familiarity with model risk management principles, including documentation standards, performance monitoring, and independent review processes.
Ability to clearly articulate complex analytical findings to both technical and non-technical audiences, including senior leadership.
Strong commitment to data accuracy, reconciliation, and quality control in a regulated environment.
Demonstrated ability to work effectively across Risk, Finance, and Analytics functions in a matrixed organization.

Nice To Haves

Experience with or knowledge of credit card, lending and/or banking industries
Experience with Python, Tableau, Alteryx, Databricks, Essbase
Experience with cloud-based data platforms (e.g., Snowflake) is a plus.
Experience with matched-pair or propensity score matching methodologies for constructing synthetic control groups.
Familiarity with credit line management strategies, including proactive and customer-requested line increase programs, and their impact on customer engagement and portfolio profitability.
Prior experience supporting model governance reviews or working within a model risk management framework at a financial institution.

Responsibilities

Build and maintain multi‑year forecasting models to estimate incremental customer engagement outcomes (outstanding balances, spend, and revolving behavior) driven by credit line management actions.
Develop and validate step‑up factor methodologies to translate Year 1 results into Year 2 and Year 3 projections using historical vintages and segmentation frameworks.
Design and apply control group approaches (e.g., holdouts, matched pairs) to isolate incremental impacts of credit strategies on customer behavior.
Incorporate recency adjustments and business judgment overlays to reflect current portfolio trends, macroeconomic conditions, and strategy changes.
Provide core engagement metric inputs (incremental balances, sales‑to‑balance, revolve rates) to Finance for multi‑year NPV and PTI calculations.
Support trimester‑based investment review processes with timely, well‑documented forecasts to evaluate profitability of credit strategy decisions.
Partner with Finance to align methodologies, reconcile assumptions, and ensure consistency between risk forecasts and financial planning outputs.
Perform ongoing performance monitoring by comparing forecasts to actual outcomes across multiple horizons (Years 1–3).
Track forecast accuracy using standardized error metrics (e.g., NMAD, MAPE), conduct stability testing of step‑up factors, and refine methodologies when thresholds are breached.
Maintain robust model governance, including comprehensive documentation, version control, approvals, audit readiness, and remediation of identified gaps.
Collaborate cross‑functionally with Risk Strategy, Finance, and Analytics partners to align assumptions, present results, obtain leadership sign‑off, and support knowledge transfer.