Kreditbee - Data Scientist (2-8 yrs)

Location: Bangalore

Experience: 12 years / 45 years

Industry: Fintech | Banking | Financial Services

About KreditBee

KreditBee is Indias largest fintech lending platform with a current monthly disbursement of over 2,200 crores. With 70 million+ downloads on the Google Play Store and 85 lakh+ unique loan customers, KreditBee offers a wide suite of digital financial services, including Personal Loans, Business Loans, Loan Against Property (LAP), DigiGold investment, Insurance, Credit Score Reports, and more. Backed by top-tier investors like Premji Invest, Advent International, MUFG, Motilal Oswal PE, and TPG-backed NewQuest, we are redefining digital credit in India.

Role Overview

We are looking for a skilled and motivated Data Scientist / ML Specialist to join our fast-growing team. This role requires working at the intersection of data science, business, and product, and contributing to data-driven strategies that enhance the customer experience and drive measurable growth.

Key Responsibilities

- Partner with leadership to align data initiatives with business goals

- Collaborate with Product, Risk, Technology, and Marketing teams

Build and refine machine learning models for:

- Customer acquisition, engagement, and retention

- Pricing, propensity, and collections strategies

- Campaign targeting and optimization

- Solve real-world problems like optimizing cost-to-collection ratios

- Conduct A/B testing, create dashboards, and deliver actionable insights

- Leverage alternate and behavioral data to improve model accuracy

- Contribute to developing risk strategies and customer segmentation frameworks

Must-Have Skills

- 12 or 45 years of hands-on experience in Data Science (Fintech/Banking preferred)

- Proven expertise in modelling for business, customer analytics and growth strategies.

- Strong problem-solving and analytical abilities

- Excellent coding and data handling skills using:

- Python

- SQL

- Comfortable working in cross-functional teams and business-driven environments

Good-to-Have

- Experience with business strategy or analytics projects

- Exposure to credit risk modeling, scorecards, or recovery analytics