Data Scientist

Quantbot; Mumbai, Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Quantbot in Mumbai, India, seeks an experienced data scientist to develop and enhance credit risk models for retail unsecured lending products such as Credit Cards and Personal Loans.

You will build propensity and channel affinity models to drive acquisition, engagement, cross-sell, and portfolio growth, while generating actionable insights through advanced analytics and ML. Collaboration with business teams is essential for measurable outcomes.

Qualifications

• Bachelor's or Master's degree in quantitative fields such as Engineering, Statistics, Mathematics, Computer Science, Economics, or related disciplines.
• Strong hands-on experience in Python, SQL, PySpark, Machine Learning, Probability & Statistics.

Responsibilities

• Develop and enhance credit risk models for retail unsecured lending products, including Credit Cards (CC) and Personal Loans (PL).
• Build propensity and channel affinity models to drive customer acquisition, engagement, cross-sell, and portfolio growth initiatives.
• Generate actionable customer insights through advanced analytics and machine learning.
• Partner with business stakeholders to translate data into impactful strategies and measurable outcomes.

Skills

Python

SQL

PySpark

Machine Learning

Probability & Statistics

Education

Bachelor's or Master's degree in a quantitative field

Job description

Batch: 2020/2021/2022/2023. Experience:

• 3-6 years
• Work across Retail Credit Risk and Marketing Data Science

Responsibilities

• Develop and enhance credit risk models for retail unsecured lending products, including Credit Cards (CC) and Personal Loans (PL)
• Build propensity and channel affinity models to drive customer acquisition, engagement, cross-sell, and portfolio growth initiatives
• Generate actionable customer insights through advanced analytics and machine learning
• Partner with business stakeholders to translate data into impactful strategies and measurable outcomes

Requirements

• Bachelor's or Master's degree in a quantitative field such as Engineering, Statistics, Mathematics, Computer Science, Economics, or related disciplines
• Strong hands-on experience in Python, SQL, PySpark, Machine Learning, Probability & Statistics