Data scientist - III/IV

Are you passionate about solving roadblocks & challenges faced by MSMEs in IndiaMSMEs contribute significantly to India’s total GDP. 90% of India’s ~$1 Trillion Retail Market is controlled by MSMEs. Which means ~$900B worth of commerce flows through these ~60M MSMEs in the form of shops/kiosks/homes, scattered all over the country. We at Khatabook, have built a product that saves time of MSMEs by managing their credit, and creating transparency in cash flow, henceforth increasing trust with their consumers and that paved the path for us to become India’s fastest-growing fintech company.Why work with us People are our biggest asset! At Khatabook, every one of us is a dynamic superstar. We have carefully bred an ecosystem which hires nothing but incredibly and exceptionally talented people who can dream, collaborate, experiment, and break new ground. We’re a strong team that looks out for each other.Your role We are seeking a highly skilled and innovative Data Scientist to strengthen our credit risk modeling team. As a Senior Data Scientist, you will be a technical leader owning high-impact machine learning solutions across the entire borrower journey. You will partner with business leaders to drive growth, manage risk, and optimize operations.What would you do at Khatabook End-to-End Borrower Lifecycle Modeling: Develop and deploy advanced machine learning solutions across the entire lending value chain, optimizing customer acquisition (propensity-to-borrow, uplift models, CAC/ROAS), strengthening credit risk underwriting (PD, LGD, risk-based pricing), and driving intelligent collections strategies (propensity-to-pay, dynamic recovery interventions). End-to-End Execution: Own the complete machine learning lifecycle, from translating ambiguous business requirements into mathematical frameworks to data pipeline creation, model training, and production deployment. Cross-Functional Leadership & Mentorship: Act as the strategic bridge between technical teams and business stakeholders (Risk, Growth, Ops). Mentor junior Data Scientists, conduct rigorous code reviews, and elevate the team’s technical standards.What are we looking for We are looking for a seasoned practitioner with a deep understanding of algorithmic development and a proven track record of solving complex problems within the financial services ecosystem. Experience: 5–8+ years of hands-on industry experience in Data Science, with a core focus on FinTech, consumer lending, or banking. Domain Expertise: Deep understanding of lending economics and the regulatory landscape. Proven experience building models for at least two of the following: marketing/growth, credit risk scorecards, or debt recovery/collections. Programming Mastery: Expert-level proficiency in Python (Pandas, Scikit-learn, NumPy) and SQL for complex data manipulation and feature engineering on large-scale datasets. Machine Learning & Statistics:Deep practical knowledge of ensemble methods (e.g., XGBoost, LightGBM, Random Forests) and foundational statistical models (Logistic Regression, Generalized Linear Models). Familiarity with survival analysis, causal inference, and experimental design (A/B testing). Big Data & Cloud Infrastructure: Experience extracting and processing large datasets using distributed computing frameworks (e.g., PySpark). Proficiency within modern cloud ecosystems (AWS, GCP, or Azure). MLOps & Deployment: Solid track record of bringing models to production. Familiarity with version control (Git), orchestration tools (Airflow), and ML lifecycle management (MLflow, CI/CD pipelines, model monitoring).