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▷ [Urgent Search] Associate Manager II - Credit Risk

▷ [Urgent Search] Associate Manager II - Credit Risk

NaviIndia
12 days ago
Job description

About the Team

The Risk team at Navi is responsible for identifying, assessing, and mitigating potential risks across the organization. The Credit Intelligence team, part of the Risk function at Navi, focuses on studying granular customer level data to gather deep insights that feedback into improving credit underwriting, as well as any strategic initiatives to enhance user engagement.

About the Role

Navi is looking for an Associate Manager II – Credit Risk to join the Group Risk function, focusing on quantitative risk management across credit portfolio and model risk. The role involves supporting the development, validation, and ongoing monitoring of credit decisioning models and underwriting strategies. You will work closely with cross-functional teams to deliver insights that guide business decisions, manage credit risk exposure, and contribute to key risk analytics initiatives including stress testing, portfolio diagnostics, and macroeconomic scenario modeling. This is a high-impact role requiring strong analytical acumen, comfort with quantitative methods, and the ability to work across both structured and exploratory problem statements.

What We Expect From You

  • Work on the Risk function mandates related to credit & model risk management, aligning to the roadmap of planned objectives across these areas
  • Support quantitative risk measurement and management initiatives for the lending business. These initiatives could include :
  • Credit model validation / monitoring
  • Review of AI / ML decision models and Underwriting Strategies
  • Portfolio health monitoring, perform RCAs to mitigate risk
  • Macro-economic modeling and loss forecasting
  • Quantification of stress testing outputs
  • Help prepare outputs of risk analytics initiatives such that engagement with Senior Management, Board Committees and external stakeholders can be facilitated
  • Assist the Group Risk function in ad-hoc quantitative modeling & risk analytics

Must Haves

  • Bachelor’s / Master’s degree, preferably with specialization in economics / statistics / quantitative finance
  • Working knowledge of AI / ML techniques in quantitative modeling
  • Proficient knowledge of SQL, Excel, Tableau. Python would be a plus
  • Experience in financial modeling would be an add-on
  • Ability to find patterns in data and analyze potential impact against key business drivers
  • Work in a dynamic environment of business, structure problems, define and track actionables
  • Excellent verbal & written communication skills, as well as presentation skills
  • Inside Navi

    We are shaping the future of financial services for a billion Indians through products that are simple, accessible, and affordable. From Personal & Home Loans to UPI, Insurance, Mutual Funds, and Gold — we’re building tech-first solutions that work at scale, with a strong customer-first approach.

    Founded by Sachin Bansal & Ankit Agarwal in 2018, we are one of India’s fastest-growing financial services organisations. But we’re just getting started!

    Our Culture

    The Navi DNA

    Ambition. Perseverance. Self-awareness. Ownership. Integrity.

    We’re looking for people who dream big when it comes to innovation. At Navi, you’ll be empowered with the right mechanisms to work in a dynamic team that builds and improves innovative solutions. If you’re driven to deliver real value to customers, no matter the challenge, this is the place for you.

    We chase excellence by uplifting each other—and that starts with every one of us.

    Why You'll Thrive at Navi

    At Navi, it’s about how you think, build, and grow. You’ll thrive here if :

  • You’re impact-driven : You take ownership, build boldly, and care about making a real difference.
  • You strive for excellence : Good isn’t good enough. You bring focus, precision, and a passion for quality.
  • You embrace change : You adapt quickly, move fast, and always put the customer first.
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