Associate Divisional Manager - Data Sciences
TVS Credit Services Ltd.
Full-time
Mathematical Science Occupations
Location
Chennai, Tamil Nadu, India
Posted
June 19, 2026
Job Description
Job Purpose:
The position is responsible to manage and lead a team of Data Scientists, developing predictive modelling solutions in credit risk and marketing for Consumer and Commercial lending portfolios
Key Responsibilities:
Provide insights, perform trend and variance analyses across the product suite for cross sell activities from a risk and marketing perspective
Assist Business teams with analyzing root cause of trends, identify incremental sales opportunities and risk mitigation avenues
Develop machine learning models, segmentation and mentor junior analysts on development of solutions that incorporate business aspects and operational constraints
Ensure operationally efficient solutions and drive optimization in existing analytics solutions
Job Requirements:
M.Tech / B.E / B.Tech / M.Sc in CS or Stats or Maths
Min of 8+ years’ experience in data science
Experience in Statistical/ Machine learning / Deep Learning Models
The position is responsible to manage and lead a team of Data Scientists, developing predictive modelling solutions in credit risk and marketing for Consumer and Commercial lending portfolios
Key Responsibilities:
Provide insights, perform trend and variance analyses across the product suite for cross sell activities from a risk and marketing perspective
Assist Business teams with analyzing root cause of trends, identify incremental sales opportunities and risk mitigation avenues
Develop machine learning models, segmentation and mentor junior analysts on development of solutions that incorporate business aspects and operational constraints
Ensure operationally efficient solutions and drive optimization in existing analytics solutions
Job Requirements:
M.Tech / B.E / B.Tech / M.Sc in CS or Stats or Maths
Min of 8+ years’ experience in data science
Experience in Statistical/ Machine learning / Deep Learning Models