Analyst - Data Science - Credit Risk Domain

Job Title: Analyst - Data Science (Credit Risk)

Location: Remote

Shift Timing: 1 PM - 9 PM IST (USA Client)

Experience: 2+ years in Credit Risk / U.S. Credit Card Analytics

Employment Type: Full-time

About Client

Client is an AI/ML-driven start-up specializing in risk analytics, data conversion, and data enrichment for financial services institutions. Headquartered in the U.S. with a delivery centre in Pune,it builds advanced AI and ML solutions for leading global financial clients.

About the Role

We are looking for analytical professionals with strong experience in credit card analytics, portfolio risk management, LTV modelling, and risk-reward trade-off modelling. The role requires hands-on experience working with U.S. credit card portfolios.

Key Responsibilities

- Develop, validate, and enhance LTV models and credit risk models.

- Build risk-reward trade-off models for portfolio and acquisition strategies.

- Analyze large datasets (internal + bureau data) to derive actionable insights.

- Lead portfolio analytics initiatives to improve credit performance.

- Perform profitability segmentation to identify customer cohorts.

- Collaborate with teams across risk, product, and marketing for credit policy design.

- Communicate analytical insights effectively to business and technical stakeholders.

Required Skills & Experience

- 2+ years of experience in U.S. credit card, consumer lending, or portfolio risk.

- Expertise in LTV modelling, risk-reward modelling, and profitability analysis.

- Strong proficiency in Python or R for statistical modelling.

- Advanced SQL skills for data extraction and processing.

- Experience with predictive modelling:

- Logistic Regression, Decision Trees, Gradient Boosting, Survival Analysis

- Familiarity with U.S. credit bureau data and scorecards.

- Strong communication and presentation skills.

Preferred Skills

- Experience with cloud platforms: AWS, GCP, Azure.

- Exposure to Spark or Databricks.

- Proficiency with visualization tools: Tableau, Power BI, Looker.

- Advanced degree in a quantitative field (e.g., Data Science, Economics, Engineering, Mathematics).

Why Join Us

- Opportunity to work end-to-end on impactful portfolio analytics projects.

- High exposure to U.S. credit card portfolios.

- Collaborate with cross-functional teams across data science, risk, and product.

- Fast-growing, innovation-driven environment.