Role: Data Scientist Credit Scoring & Analytics Implementation

Hands-on experience : Machine Learning model implementation and deployment, SQL, Python.

Key Responsibilities
Lead the design, development and validation of credit risk scorecard models using ML, AI,and other statistical techniques, using Financial and Alternate Data.
Perform advanced exploratory data analysis (EDA), feature engineering, and data preparation on large, complex datasets
Translate business and risk requirements into analytical solutions and support their integration into production systems. (e.g., AUC, KS, Gini)
Own end-to-end model lifecycle: development, validation, deployment and ongoing monitoring
Partner with engineering teams to integrate models into production systems (APIs, batch scoring,real-time decisioning) and collaborate with application teams to ensure robust and scalable implementation of scoring logic
Develop monitoring frameworks, dashboards, and reports to track model performance, drift and portfolio health
Produce high-quality technical documentation, validation reports, model reports and stakeholder presentations
Provide technical guidance, best practices and task allocation to team members and support knowledge transfer across teams.





Required Technical Skills

Must Have
810 years of experience in ML models implementation & credit risk technology solutions
Deep understanding of statistical modelling techniques (logistic regression, WOE/IV, binning, model validation) and machine learning methods
Strong proficiency in Python (preferred) or similar analytical tools (e.g., SAS, STATA)
Solid understanding of .NET / C# based applications and system integration
Advanced SQL skills and experience working with large-scale relational databases (e.g., Oracle,SQL Server, Postgres and MongoDB)
Experience managing analytics or technology delivery projects
Robust communication skills

Valuable to Have
Basic understanding of credit risk modelling / scorecard concepts
Familiarity with BI and visualization tools such as Power BI
Knowledge of regulatory frameworks in credit risk (e.g., IFRS 9, Basel III)
Experience with cloud platforms (AWS, Azure, or GCP)

Impact
Drive credit risk strategy through robust, production-grade models
Improve portfolio performance and decision accuracy

Shape best practices in model development, deployment, and monitoring

📌 Senior Data Scientist Chennai
🏢 Dun & Bradstreet Technologies and data services
📍 Chennai