Analyst - Data Science

blu Cognition is an AI-powered commercial credit intelligence company serving lenders and financial institutions. Our platform combines commercial credit data contributed by 150+ lenders with AI-driven analytics, banking data and fraud detection to help our clients make faster, better credit decisions. Our product suite includes blu Sense, which converts bank statements into standardized, categorized transaction data with real-time financial insights, and Fraud Lens, which detects document tampering and first-party fraud.

Alongside our data products, we run a managed services business supporting underwriting, fraud review, and KYC/KYB and sanctions screening operations for our clients, with teams across North America, Asia and Europe.

blu Cognition is an AI-powered commercial credit intelligence company serving lenders and financial institutions. Our platform combines commercial credit data contributed by 150+ lenders with AI-driven analytics, banking data and fraud detection to help our clients make faster, better credit decisions. Our product suite includes blu Sense, which converts bank statements into standardized, categorized transaction data with real-time financial insights, and Fraud Lens, which detects document tampering and first-party fraud.

Alongside our data products, we run a managed services business supporting underwriting, fraud review, and KYC/KYB and sanctions screening operations for our clients, with teams across North America, Asia and Europe.

We are looking for analytically strong professionals with deep expertise in credit card analytics, portfolio management, and risk strategy particularly those who have worked on LTV (Lifetime Value) and Risk Reward trade-off modelling.

The ideal candidate brings experience working with U.S. credit card portfolios and can connect data-driven insights to business profitability and portfolio health.

• Develop, validate, and enhance LTV models, credit risk models, and portfolio profitability frameworks.
• Work on Risk Reward trade-off modelling to optimize acquisition and portfolio strategies-balancing growth and default risk.
• Extract and explore data, validate data integrity, perform ad hoc analysis, evaluate new data sources for usage in strategy development.
• Lead portfolio analytics initiatives to track and improve credit performance.
• Partner with risk, product, and marketing teams to design data-driven credit policies, limit strategies, and customer lifecycle interventions.
• Conduct profitability segmentation to identify high-value and high-risk customer cohorts.
• Support pricing and credit limit optimization using predictive modelling and scenario simulations.
• Analyse large-scale datasets (internal + bureau data) to extract actionable insights for portfolio health monitoring.

• 2 years + of experience in credit card, consumer lending, or portfolio risk space.
• Proven experience in LTV modelling, risk-reward trade-off, and portfolio profitability optimization.
• Hands-on proficiency in Python or R for statistical modelling and SQL for data extraction/manipulation.
• Expertise in predictive modelling (logistic regression, decision trees, gradient boosting, survival analysis).
• Experience with credit bureau data, scorecards, and portfolio forecasting techniques and familiarity with U.S. credit systems.
• Ability to communicate findings clearly to both technical and business audiences.

• Degree from a top-tier institution;
  Particularly in a quantitative field (e.g., computer science, data science, engineering, economics, mathematics, etc.). Advanced degree preferred.

• Work on end-to-end credit portfolio analytics driving real financial outcomes.
• Exposure to U.S. credit card portfolios and data-driven risk strategy.
• Collaborate with cross-functional teams across risk, marketing, and product to shape growth and profitability.