Credit Risk Manager

5 days ago

Bangalore Urban, India Taglynk Full time

What You Will Do:

Credit Policy Analysis:

  • Analyze credit policies using platform data, bureau data, and alternate data.
  • Create scorecards and models (Application Score, B-Score, Collection Scores).
  • Design experiments to test cohort behavior and experimental policies.
  • Identify leading indicators and Early Warning Signals (EWS).
  • Automate reporting and tracking of portfolio performance across multiple levels, including operations performance measures, key performance indicators, and associated drivers.

Long-term Responsibilities:

  • Refine credit policies based on data and create new policies to lend in unexplored segments.
  • Develop ML model methodologies: feature creation, development, tuning, validation, monitoring, calibration, and strategy creation.
  • Code Business Rule Engines (BRE), automate credit policies, and make underwriting decisions as needed.

What You Will Need:

  • Experience:
  • 4-8 years of relevant FinTech experience, preferably in Digital Unsecured Lending, with products like business loans (SME), BNPL, and PL (Consumer).
  • Proven ability to drive and conceptualize projects on Risk and Data Science.

Skills:

  • Strong Root Cause Analysis (RCA) skills and excellent critical thinking abilities.
  • Ability to present your beliefs clearly and compellingly, both verbally and in written form.
  • Working knowledge of SQL, Big Data systems like Hive, Metabase, or other databases for data mining in structured and unstructured data analytics.
  • Expertise in Probability of Default (PD), Exposure at Default (EAD), and Loss Given Default (LGD) modeling in a Python environment.
  • Ability to thrive in a fast-paced, collaborative environment.

Education:

  • Engineering or Master’s degree in Statistics or Data Science.
  • Prior experience in a fast-paced Credit Risk Policy, Risk Analytics, or Decision Science team.

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