Lead Data Scientist — FameScore (MSME Credit Score)
FINAGG Technologies Private Limited
Location
🇮🇳 Noida, India
Type
full_time
Salary
Undisclosed
Posted
3w ago
Job Description
Company Description FINAGG Technologies Private Limited is a fast-growing fintech organization focused on building and financing one of India’s largest distributor and retailer networks. Led by seasoned professionals with deep experience in the finance industry and successful exits from VC-funded ventures, the company combines strong domain expertise with innovation. FINAGG’s platform is trusted by over 20 major corporate houses in India and is actively disrupting the traditional lending market. The company places SME/MSME businesses and retailers at the center of its mission, supporting the growth of Atmanirbhar Bharat. Team members join a dynamic environment dedicated to strengthening the country’s creation and consumption ecosystem. Role Description The Lead Data Scientist — FameScore (MSME Credit Score) is a full-time on-site role based in Noida. This role is responsible for designing, developing, and refining credit scoring models for MSMEs using advanced data science, statistics, and analytics techniques. Day-to-day tasks include gathering and preprocessing data from multiple internal and external sources, performing exploratory data analysis, building and validating predictive models, and translating insights into actionable product and risk strategies. The Lead Data Scientist collaborates closely with engineering, product, risk, and business teams to operationalize models, monitor performance, and ensure regulatory and compliance standards are met.
The role
also involves mentoring junior data team members, driving best practices in model governance and documentation, and contributing to the continuous improvement of the FameScore framework.
Qualifications
- Strong foundation in Data Science and Statistics, with experience applying these disciplines to risk modeling, credit scoring, or financial services.
- Proficiency in Data Analytics and Data Analysis to extract insights, identify patterns, and support data-driven decision-making.