Principal Associate, Business Analysis

Capital One Capital One · Banking · Bangalore, IN

This role focuses on applying advanced data methodologies, statistics, and machine learning models within the Anti-Money Laundering (AML) domain. The Principal Associate, Business Analysis will be responsible for understanding user needs, conducting business analyses, defining business requirements, and executing against product strategy to modernize how Capital One identifies potential financial crimes. While the role involves working with ML models and data, the primary output is business strategy, product definition, and requirements, rather than shipping the ML models themselves.

What you'd actually do

  1. Develop business strategies that will drive growth, profitability, and competitive success for Capital One in the face of shifting consumer and regulatory demands.
  2. Manage and sequence delivery of business intent, build business requirements and execute against the product strategy.
  3. Work closely with colleagues across Capital One including: Tech, Model Risk, Lines of Business, and others to drive improvement in quality, volume, service, and profitability.
  4. A proven track record of decision making and problem solving based on analytics.
  5. May manage and develop analysts.

Skills

Required

  • Bachelor's Degree in a quantitative field (Statistics, Math, Engineering, Economics, Econometrics, Finance, or Operations Research)
  • At least 5 years of professional work experience in analytics, business analysis, or data-driven product management
  • Python
  • R
  • SQL
  • relational databases
  • key econometric and statistical techniques
  • model design, development, and deployment
  • Excellent written and verbal communication skills

Nice to have

  • Experience in the financial services industry, specifically dealing with cross-LOB operations or customer experience
  • Proven experience translating high-level business strategy and advanced analytics into tangible products and actionable outcomes.
  • Experience in Fraud / Anti-money Laundering domain.

What the JD emphasized

  • quantitative field
  • analytics
  • business analysis
  • data-driven product management
  • advanced analytic techniques
  • statistics
  • machine learning models
  • Statistical / ML models
  • advanced analytics
  • model design, development, and deployment

Other signals

  • advanced analytic techniques
  • statistics
  • machine learning models
  • data sourcing
  • predictive models
  • business requirements
  • Statistical / ML models
  • advanced analytics
  • model design, development, and deployment