Senior Risk Manager

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.

Who we're looking for

We are seeking a data-driven Senior Manager – Risk & Analytics with 8+ 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 the next generation of AI-native credit decisioning at Jupiter.

This is a high-impact role sitting at the intersection of Risk, Analytics, Product, and Business. You will own execution of credit risk strategy, from underwriting design and portfolio monitoring to advanced predictive modelling as we scale our business vertically as well as horizontally. You will also be playing important role in GenAI-augmented decisioning, and policy governance directly influencing 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.

This role reports directly to the Head of Risk & Analytics and is being built as the function's key hiring, as Jupiter continues to expand and scale. You will play a central role in widening the scope and depth of the Risk & Analytics function as we grow.

Roles and responsibilities

1. Credit Risk Strategy & Portfolio Ownership

• Own execution of credit risk strategy across Personal Loans, Embedded finance and other unsecured lending products, with direct input into overall policy direction as the function scales
• 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
• Identify 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 teams2. 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 alignment
• 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 performance3. Credit Analytics, Measurement & Experimentation
• Own end-to-end analytics workflows: data extraction → modelling/insight → strategy design → post-impact measurement
• 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 analysis4. 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
• 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 reviews

6. Leadership & Cross-Functional Collaboration

• Directly manage and grow a team of analysts/data scientists; owning hiring, performance, and career development while setting analytical standards and best practices across the function
• Partner closely with Product, Engineering, Data Science, Operations, and Compliance teams
• Provide credit risk leadership during new product launches, feature rollouts, and strategic experiments
• Act as proxy for the Head of Risk & Analytics in governance forums, senior stakeholder reviews, and cross-functional leadership discussions, deputizing as needed as the function scales
• Translate complex risk and fraud insights into business-friendly narratives for senior stakeholders

What we're looking for

Core requirements

• 8+ years of experience in credit risk analytics, underwriting strategy, or portfolio risk management
• Strong hands-on expertise in SQL and Python for large-scale data analysis and modelling
• Proven experience building and deploying predictive / ML-based credit risk models
• Deep understanding of bureau data, transactional data, and alternative data sources
• Strong grounding in model validation, stability monitoring, and explainability
• Strong capabilities to support AI-native risk systems
• Excellent structured problem-solving and analytical rigor
• Ability to clearly communicate insights to non-technical and senior stakeholders
• Strong ownership mindset with the ability to operate in fast-paced, high-growth environmentsPreferred
• Prior experience scaling credit systems or underwriting platforms in fintech or high-growth lending businesses
• Exposure to multiple product types (PL, Cards, BNPL, LAP, Secured Lending)
• Working knowledge of Generative AI / LLMs for risk and underwriting use cases — e.g. prompt engineering, LLM-assisted decisioning or agentic workflows, RAG-based policy/document reasoning, or evaluating LLM outputs for credit and fraud use cases
• Familiarity with AI/ML governance and responsible-AI practices in a regulated (BFSI) context