Risk Manager

Job description

**What we do** Money. It's always on our mind and often comes with a rollercoaster of emotions and complex jargon. That's why at Jupiter, our mission is to improve your financial well-being by giving you full control over your money, helping you track, save, and invest with confidence. We're a financial services platform that uses technology to simplify money management. Whether it's a savings account, payments, loans, credit cards, investments, or smart money tools — it's all on Jupiter. We break down banking jargon, offer spending insights, and give users modern features to make better financial decisions. **Our journey** Jupiter was founded in 2019 by Jitendra Gupta (founder of Citrus Pay), who saw how broken personal finance felt compared to customer-first experiences like food or entertainment. We launched in 2021 with a 100,000+ waitlist. Today, 30 Lakh+ users trust us with their money .We've built a team of creative thinkers and domain experts, driven by a shared vision of a transparent and inclusive financial ecosystem. We've embraced cutting-edge technology with high ownership and deep customer obsession. Our team, spanning Mobile, Platform, Data, AI & ML, is building to scale products across the board. From AI to behavioral science, we're creating world-class banking experiences, and we're looking for more builders to join us. **Who we're looking for** We are seeking **a data-driven Manager – Risk & Analyti** cs with 5+ years of strong experience in credit risk analytics, underwriting strategy, and advanced modelling to lead and scale our risk capabilities across multiple lending products — and to help build th **e next generation of AI-native credit decisioni** ng at Jupiter.This is a high-impact leadership role sitting at the intersection o **f Risk, Analytics, Product, and Busine** ss. You will own end-to-end credit risk strategy — from underwriting design and portfolio monitoring to advanced predictive modelling, GenAI-augmented decisioning, and policy governance — directly influencin **g credit losses, growth efficiency, customer experience, and long-term portfolio quality** .You will lead complex analytical initiatives, mentor analysts/data scientists, and act as a trusted advisor to senior stakeholders while shaping the evolution of our credit decisioning systems — including our move toward agentic and LLM-assisted underwriting — in a high-growth environment. **Roles and responsibilities** **1. Credit Risk Strategy & Portfolio Ownership** - Own and evolve credit risk strategy across Personal Loans, BNPL, credit cards, and other unsecured lending products - Lead underwriting framework design including policy rules, score cut-offs, limit assignment logic, and risk-based pricing - Monitor portfolio health using vintage analysis, roll rates, PD/LGD trends, early delinquency indicators, and loss curves - dentify emerging risks, adverse selection, and structural weaknesses using statistical and ML-driven approaches - Translate analytical insights into clear, actionable recommendations for Product, Business, and Leadership teams **2. Predictive Modelling & Advanced Analytics** - Lead development, validation, and deployment of credit risk models, including - Probability of Default (PD) - Early Delinquency / First EMI Default - Limit assignment & line management - Risk-based pricing & segmentation - Drive feature engineering using bureau data, transactional behavior, alternative data (device/digital footprint, Account Aggregator data), and lifecycle signals - Guide and review ML approaches (logistic regression, tree-based models, gradient boosting, etc.) with a focus on explainability and business alignments - Define and oversee model performance and stability monitoring using AUC, KS, Gini, PSI, back-testing, and drift metrics - Recommend model recalibration, retraining, or strategic overlays based on portfolio performance **3. Credit Analytics, Measurement & Experimentation** - Own end-to-end analytics workflows: data extraction → modelling/insight → strategy design → post-impact measurements - Optimize approval rates, risk-adjusted returns, customer profitability, and portfolio ROI through deep data analysis - Define, track, and review key credit KPIs: DPD metrics, NPA rates, loss rates, approval efficiency, and cohort performance - Design and evaluate policy and model experiments using controlled testing and cohort analysis **4. AI & GenAI-led Risk Innovation** - Contribute to the design of AI-native underwriting systems — combining bureau, alternate data, and conversational/LLM-based signal extraction - Explore GenAI use cases across borrower persona prediction, boundary/edge-case resolution, and policy-document reasoning for credit decisioning - Partner with Data Science/Engineering to responsibly evaluate LLM-assisted underwriting agents — balancing model performance, explainability, and regulatory expectations - Help define guardrails, monitoring, and governance for AI/ML systems used in credit decisions, in line with evolving regulatory guidance (e.g. RBI Model Risk Management expectations **5. Credit Policy, Governance & Controls** - Lead continuous improvement of credit policies across onboarding, pricing, limits, and lifecycle management - Conduct root-cause analysis for portfolio deterioration, model drift, or unexpected loss spikes - Ensure strong documentation of models, policies, assumptions, and decision frameworks - Support regulatory audits, model governance forums, and internal risk review **6. Leadership & Cross-Functional Collaboration** - Mentor and guide analysts/data scientists; set analytical standards - Partner closely with Product, Engineering, Data Science, Operations, and Compliance teams - Provide credit risk leadership during new product launches, feature rollouts, and strategic experiments - Translate complex risk and fraud insights into business-friendly narratives for senior stakehold **ers** **What we're lookingforCore re