Data Scientist

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.