Job Description
About Cashera Cashera is a fast-growing fintech and lending company that provides funding solutions to businesses across multiple industries in the United States and UK. Cashera combines technology, data-driven decision-making, and industry expertise to deliver fast, adaptable financing options that traditional lenders often cannot provide. The Role As a Senior Data Scientist on the Credit & Fraud Risk Team, you will take ownership of the end-to-end lifecycle of predictive machine learning models. You'll play a foundational role in building systems that evaluate borrower creditworthiness, mitigate operational loss, and intercept real-time fraud vectors. This is a business-critical position reporting directly to Risk and Data Science Leadership, collaborating closely with Engineering, Product, Collections, and Finance teams. Key Responsibilities • Model Development & Lifecycle: Build, evaluate, and scale predictive models using XGBoost, LightGBM, and Deep Learning for underwriting, credit line assignment, and collections.



Familiarity with gen-AI techniques for feature creation and transaction tagging on bank transactional data is a plus. • Credit Risk Modeling: Build credit risk models for sub-prime and near-prime customers in a fintech environment with short model build cycles. • Fraud & Risk Defense: Design and deploy real-time decisioning rules and ML systems to detect synthetic fraud, digital identity theft, account takeovers, and transactional fraud. • Feature Engineering: Mine complex, large-scale, and alternative data streams (bank transactional data, logs, credit bureau reports, structured/unstructured digital signals) to extract predictive signals. • Portfolio Optimization: Partner with Credit Risk Strategists to translate model outputs into actionable credit limits, cutoff thresholds, and loss-forecasting simulations. • Platform Architecture: Collaborate with Data Platform Engineers to build reliable pipelines and high-throughput feature extr

📌 Senior Data Scientist (Mumbai)
🏢 Cashera
📍 Mumbai