Principal Associate, Data Science

Capital One · Banking · Bangalore, IN

This role is in Model Risk Management for Retail Banking, focusing on independent validation and technical challenge of state-of-the-art models, including ML and Generative AI, for domains like Fraud, Deposits, and Generative AI. The role involves partnering with developers, building tools for model evaluation, and communicating complex findings. It requires strong statistical and ML knowledge, experience with Python/R, and ideally, experience in financial services, Fraud, or Generative AI.

What you'd actually do

  1. Assess and challenge state-of-the-art decision-making models, including ML and Gen AI, to internal stakeholders and regulatory partners.
  2. Partner cross-functionally with model developers, business analysts, and tech teams to enable the safe capturing of risky behavior while influencing broader business strategies.
  3. Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives. Collaborate with Quants and Data Scientists to drive innovation and research in advanced modeling space, leading to high-performing benchmark model development.
  4. Build data products and custom software tools for automated model performance evaluation, back-testing, and data exploration using open-source and cloud platforms.
  5. Utilize your statistical toolset to mine complex, voluminous data sources, providing meaningful insights on business strategies through rigorous model assessment.

Skills

Required

  • Bachelor’s degree in statistics, math, engineering, economics, econometrics, financial engineering, finance, or operations research with a quantitative focus.
  • At least 4 years of experience in data analytics.
  • At least 3 years of experience in Python or R.

Nice to have

  • Proficiency in key econometric and statistical techniques (such as predictive modeling, logistic regression, panel data models, decision trees, machine learning methods)
  • 4+ years of experience model development or validation
  • 4+ years of experience in R or Python for large scale data analysis
  • 4+ years of experience with relational databases and SQL
  • Strong analytical skills with high attention to detail and accuracy
  • Excellent written and verbal communication skills
  • Experience in financial services industry
  • Experience in Fraud Domain and Generative AI

What the JD emphasized

  • Independent Validation and Challenge
  • state-of-the-art models
  • ML and Gen AI
  • Fraud
  • Deposits
  • Generative AI
  • model performance evaluation
  • model integrity
  • regulatory compliance
  • stringent industry standards

Other signals

  • Model Risk Management
  • validation and challenge
  • Generative AI
  • Fraud
  • Deposits