Risk Analytics Specialist

Job Summary

We are looking for a skilled and driven Credit Risk Analytics Officer to join our Credit Risk & Analytics team. This role is ideal for professionals with hands-on experience in credit risk analytics, statistical modeling, and data-driven decision-making within the Banking, Financial Services, and Insurance (BFSI) industry.

The successful candidate will play a key role in developing and enhancing credit scorecards, supporting risk strategy formulation, and driving data-driven decisions across the customer lifecycle. This is a high-impact opportunity to work closely with leadership and help build a strong in-house analytics capability.

Key Responsibilities

• Support the development and enhancement of credit risk models.
• Perform end-to-end model lifecycle activities, including data preparation, exploratory data analysis, feature engineering, model development, validation, and monitoring.
• Translate analytical insights into actionable credit strategies, including cut-offs, credit limit setting, and customer segmentation.
• Conduct portfolio analytics to identify risk trends, early warning signals, and optimization opportunities.
• Support analytics initiatives across Marketing, Acquisition, Behavioral, and Collections strategies.
• Develop and maintain analytical datasets while ensuring data quality and integrity using Python, R, SAS, or SQL.
• Prepare dashboards, reports, and presentations for senior management.
• Collaborate with Credit Operations, IT, and other business units to ensure successful implementation and data integrity.
• Coordinate with external partners on model validation and deployment activities.

Qualifications

• Bachelor's or Master's degree in Statistics, Mathematics, Economics, Engineering, Data Science, or a related quantitative field.
• 2–7 years of experience in analytics, preferably within the BFSI or Credit Risk domain.
• Hands-on experience in credit risk model development, particularly Probability of Default (PD) models. Experience with Exposure at Default (EAD) and Loss Given Default (LGD) models is an advantage.
• Experience in portfolio analytics and credit risk strategy development.
• Strong analytical and problem-solving skills with the ability to interpret complex datasets.
• Proficiency in Python, R, SAS, SQL, or other analytical tools.
• Excellent communication and stakeholder management skills.