Data Scientist – Banking & Credit Risk

Job Summary

Data Scientist

Key Responsibilities

• Design, develop, and maintain
• credit risk models
• , including application, behavior, and collection scorecards.
• Analyze large-scale banking datasets related to
• loans, credit portfolios, delinquencies, and defaults
• .
• Work closely with risk, compliance, and business teams to support
• loan decisioning and risk strategies
• .
• Develop and optimize
• scoring platforms
• and automated decisioning frameworks.
• Perform
• model validation, monitoring, and performance tracking
• to ensure regulatory and business compliance.
• Translate complex analytical outcomes into clear insights and recommendations for stakeholders.
• Ensure adherence to
• banking regulations and risk governance standards
• .
• Support end-to-end model lifecycle including documentation, approvals, and audits.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in

Data Science, Statistics, Mathematics, Computer Science, Economics

• , or a related field.
• Proven experience as a
• Data Scientist within the banking or financial services sector
• .
• Strong hands-on experience with
• credit risk, loan analytics, scorecards, and scoring platforms
• .
• Expertise in
• statistical modeling techniques
• (e.g., logistic regression, decision trees, survival analysis).
• Proficiency in

Python, R, or SAS

• for data analysis and modeling.
• Experience working with

Sql

• and large relational databases.
• Solid understanding of
• credit policies, loan lifecycle, and risk metrics
• (PD, LGD, EAD preferred).

Preferred Qualifications

• Experience with
• alternative data
• and advanced ML techniques in credit risk.
• Familiarity with
• model governance, regulatory frameworks, and audits
• in banking.
• Exposure to
• retail banking products
• , including personal loans, auto loans, credit cards, or mortgages.
• Strong communication skills with the ability to explain technical results to non-technical stakeholders.

What We Offer

• Opportunity to work on
• high-impact banking and risk analytics projects
• .
• Collaborative and data-driven work environment.
• Competitive compensation and benefits.
• Career growth within analytics, risk, and AI functions.