Director, Credit Risk Strategy - Returning Customer Channel

About the Role:

We are looking for a seasoned credit risk leader to own the full lifecycle of credit strategy for our Returning Customer personal loan channel. From re-underwriting and offer generation through in-life account management, pricing, line decisions, and servicing strategy, you will set the vision and drive execution for how we engage, underwrite, and manage existing customers.

You will lead with data-guiding the deployment of machine-learning models, alternative data sources, and advanced analytics to grow the portfolio profitably while keeping credit and fraud losses within appetite. You will also serve as the senior credit strategy partner across Finance, Capital Markets, Product, Engineering, Legal, Compliance, Operations, Marketing, and Fraud, and build a high-performing team of strategists and data scientists based in India while working closely with US-based stakeholders.

What You Will Own:

- Returning Channel Credit Strategy & Roadmap: Design and evolve the credit, pricing, and verification strategy for returning borrowers-including re-underwriting eligibility, pre-approval and pre-qualification workflows, offer generation, cross-sell/up-sell, and refinance/consolidation programs. Balance loss, approval rate, take-rate, unit economics, and customer experience to hit portfolio targets.

- Account & Line Management: Build and run in-life account management strategies such as credit line increases and decreases, APR repricing, authorization logic, over-limit tolerance, retention campaigns, and dormant-account reactivation. Ground decisions in behavioral scores, bureau triggers, and payment patterns.

- Servicing & Collections Partnership: Work hand-in-hand with Servicing and Collections to optimize the trade-off between collections effort and returning-customer strategy. Ensure loss-mitigation actions, right-party treatments, and post-delinquency decisions reinforce lifetime value rather than erode it, and align treatments with credit segmentation and expected loss.

- ML/AI & Alternative Data Innovation: Direct the development and rollout of ML/AI credit and behavioral models, champion/challenger scorecards, and alternative data to sharpen underwriting precision and improve returns.

- Risk Appetite & Loss Forecasting: Keep credit losses inside the company risk appetite; oversee vintage-level loss forecasting and roll-rate analytics for the Returning book.

- Policy, Rule & Decisioning Governance: Govern credit policy, rules, cutoffs, and decisioning thresholds end-to-end. Establish standards for proposal, review, approval, deployment, monitoring, retirement, and change control with clear sign-off across Risk, Compliance, and Operations.

- Portfolio Monitoring & Segment Analytics: Continuously analyze portfolio performance at a granular level-by vintage, FICO/Vantage/Clarity band, product, term, loan amount, channel sub-segment, and state-to spot emerging trends, isolate key drivers, and trigger strategy actions.

- Executive Communication: Deliver data-driven recommendations to executive leadership and the Credit Risk Committee, turning complex credit analytics into clear, compelling narratives.

- Cross-Functional Collaboration: Partner with Finance, Portfolio Management, Capital Markets, Product, Marketing, Operations, Legal, Compliance, Engineering, and Fraud to design, implement, and monitor high-performing strategies.

- Vendor & Capability Evaluation: Identify, assess, and build business cases for new bureaus, alternative data providers, verification vendors, and emerging technologies.

- Test-and-Learn Discipline: Institute a robust experimentation culture-champion/challenger tests, policy back-tests, holdouts, A/B and multivariate tests, and uplift measurement-to quantify how strategy changes affect loss, approval, take-rate, and downstream lifetime value.

- Regulatory & Compliance Alignment: Ensure Returning channel credit strategy adheres to applicable US consumer lending regulations and guidance.

- Team Leadership: Lead, mentor, and expand a distributed team of credit strategists, analysts, and data scientists across the US and India.

What You Bring:

- Education: Bachelor degree in a quantitative discipline (Statistics, Computer Science, Mathematics, Economics, Engineering, or related); advanced degree preferred.

- Experience: 12+ years managing credit risk in the Credit Card or Personal Loan space, with deep expertise in credit and fraud risk management and strong business acumen; loss forecasting experience is a strong plus.

- Returning-Book Expertise: Proven track record owning credit strategy for returning or existing customers.

- Servicing & Line Management Acumen: Hands-on familiarity with account management, line management, and servicing/collections strategy.

- Model & Scorecard Fluency: Solid working knowledge of ML/AI credit and behavioral models.

- Technical Skills: Proficiency in SQL and at least one of Python or R. Comfortable with cloud data warehouses (Snowflake, Databricks, Redshift), BI/visualization tools (Tableau, Looker, Power BI), and modern decisioning platforms.

- Leadership: 7+ years of people-management experience, with a demonstrated ability to mentor, develop, and inspire high-performing, innovative teams.

- Regulatory Knowledge: Working knowledge of US consumer lending regulation and model risk management (SR 11-7 principles).

- Communication: Exceptional written and verbal communication skills.

What Success Looks Like in Year One:

- A documented Returning channel credit strategy roadmap aligned to loss, approval, take-rate, and LTV KPIs.

- A refreshed account management and line management framework in production, delivering measurable lift.

- An optimized Servicing-Collections partnership that improves the trade-off between collections effort and returning-customer LTV.

- An upgraded ML/AI model and alternative data stack with clear performance attribution.

- An executive- and investor-ready monthly credit pack and Credit Risk Committee narrative in regular production.