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Senior Manager -Risk and Analytics

Jupiter

5 - 10 years

Bengaluru

Posted: 12/02/2026

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Job Description

What we do:

Money. It's always on our mind and often comes with a rollercoaster of emotions and complex jargon. Thats 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.

Were a financial services platform that uses technology to simplify money management. Whether its a savings account, payments, loans, credit cards, investments, or smart money tools its 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.

Weve 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, were creating world class banking experiences, and were looking for more builders to join us.


Who we're looking for:


We are seeking a data-driven Senior Manager Risk & Analytics with 7+ years of strong experience in credit risk analytics, underwriting strategy, and advanced modelling to lead and scale our risk capabilities across multiple lending products.

This is a high-impact leadership role sitting at the intersection of Risk, Analytics, Product, and Business. You will own end-to-end credit risk strategy from underwriting design and portfolio monitoring to advanced predictive modelling 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 in a high-growth environment.



Roles and Responsibilities:

Credit Risk Strategy & Portfolio Ownership

  • Own and evolve credit risk strategy across Personal Loans, Credit Cards, BNPL, LAP, and other secured/unsecured 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
  • 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 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, 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 performance

3. Credit Analytics, Measurement & Experimentation

  • Own end-to-end analytics workflows: data extraction modeling/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 analysis

4. 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

5. Leadership & Cross-Functional Collaboration

  • Mentor and guide analysts/data scientists; set analytical standards and best practices
  • 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 stakeholders


What Were Looking For


  • 7+ 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
  • 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 environments



Preferred / Brownie Points

  • 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)
  • Academic background from IIT / NIT or equivalent, with strong hands-on analytical depth


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