Note: The job is a remote job and is open to candidates in USA. Flex is building an AI-native private bank for business owners, aiming to re-architect the financial system for entrepreneurs. The Portfolio Risk Analytics Lead will oversee end-to-end portfolio risk analytics for Flex's credit card book, providing insights that inform credit decisioning and management frameworks.
Responsibilities
- Own end-to-end portfolio risk analytics for Flex's credit card book across small business and consumer segments — end-to-end meaning full lifecycle visibility, from pre-acquisition through charge-off:
- Acquisition & application flow: attribution of applicant volume by channel and marketing source; approval rate and decline reason analysis; segmentation of the incoming credit population to inform policy calibration
- Credit policy & line assignment: analyze approval thresholds, bureau cutoff performance, and risk-tiered line sizing; identify where policy is over- or under-serving the target credit population
- Multi-relationship context: incorporate existing Flex relationship data — payment history, product usage, behavioral signals — into credit decisioning and line management frameworks
- Spend, authorization & usage: monitor authorization patterns, spend velocity, and category mix as leading indicators of both credit quality and fraud risk; identify anomalies at the obligor and segment level
- Payment behavior & utilization: track minimum payment rates, payment-to-balance ratios, revolve propensity, and utilization trends as core indicators of borrower stress or strength
- Portfolio performance & loss: maintain vintage curves, roll rate matrices, and delinquency migration analysis; own loss forecasting and reserve calibration inputs
- Charge-off & recovery: analyze loss emergence patterns by segment, vintage, and acquisition cohort; incorporate recovery expectations into net loss projections
- Build and maintain early warning frameworks that surface emerging credit deterioration before it appears in lagging indicators — translating behavioral and transactional signals into actionable portfolio triggers
- Synthesize data across sources — financial statements, open banking, 3rd party, transaction-level, behavioral, and macro — to construct a coherent view of portfolio health; fill analytical gaps intelligently when data is sparse or contradictory
- Lead periodic portfolio reviews: design the analytical narrative, own the underlying data, and present findings with clear risk implications to credit committees and senior leadership
- Develop credit risk segmentation — by industry, vintage, utilization band, payment behavior, and obligor type — to enable more precise limit management, pricing, and loss reserve calibration
- Partner cross-functionally with Underwriting, Engineering, Product, Finance, and L&C to ensure portfolio risk visibility is embedded in upstream decisions, not surfaced reactively
- Contribute to stress testing and scenario analysis: model portfolio performance under adverse conditions and translate output into concrete exposure and loss estimates
- Serve as the internal SME on credit card analytics — establishing standards for how the portfolio is measured, reported, and interpreted as the book scales
Skills
- 7–15 years of hands-on credit card risk analytics experience across consumer and small business
- Direct exposure to both a bank or bank-issued program and a fintech lender strongly preferred
- Subject matter expertise in credit card metrics — vintage curves, roll rates, loss forecasting, utilization dynamics, payment hierarchy — built through direct ownership of these analyses, not observation
- Analytically self-sufficient: proficient in SQL and Python or R, comfortable working with large and messy datasets, and capable of building from raw data rather than consuming pre-built dashboards
- Understands the distinct analytical demands of SMB credit: cash flow seasonality, owner-business financial entanglement, and the limits of bureau data for thin-file entities
- Operates at a senior thinking level relative to peer cohort — brings a point of view, challenges assumptions, and moves without waiting to be directed
- High quantitative aptitude with strong intuition for when outputs don't pass the smell test; catches anomalies early
- High-energy, end-to-end owner who thrives in environments where infrastructure is still being built and the analytical agenda isn't fully handed to you
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