Role Summary
Own the vision, strategy, and execution of TapLend's Data Science function by building and scaling a high-performing team, driving AI and analytics initiatives, and delivering scalable machine learning solutions across underwriting, credit risk, fraud detection, collections, and lending operations.

Key Responsibilities
● Lead, mentor, and scale the Data Science and Analytics team.
● Define and execute the AI and Data Science roadmap aligned with business objectives.
● Design, build and deploy machine learning models for credit risk, fraud detection, affordability assessment and customer behavior.
● Develop AI-powered solutions for underwriting, collections, customer support and operational automation.
● Own the end-to-end machine learning lifecycle, including feature engineering, model development, deployment, monitoring and continuous improvement.
● Partner closely with Product, Risk, Engineering and Business teams to deliver measurable business impact.
● Present strategic insights, model performance and recommendations to senior leadership.




● Drive innovation by evaluating and adopting emerging AI and Generative AI technologies.
● Establish best practices for experimentation, model governance and AI development.
● Hire, mentor and retain top Data Science talent. Technical Skills
● Python, SQL, Pandas, NumPy
● Machine Learning: XGBoost, LightGBM, CatBoost, Scikit-learn
● Credit Risk Analytics, Scorecards, PD/LGD concepts, Bureau Analytics
● Fraud Detection, Portfolio Analytics, Affordability & Early Warning Models
● ClickHouse, PostgreSQL, MySQL, Spark
● Power BI, Tableau or Grafana Positive to Have Skills
● Experience with LLMs, AI Agents, RAG, LangChain, LangGraph, LlamaIndex or similar frameworks.
● Knowledge of Credit Risk Modelling, Credit Bureau data and lending analytics.
● Exposure to MLOps, Docker, Cloud platforms (AWS/Azure/GCP) and production ML systems.

Qualifications
● Bachelor's/Master's degree in Computer Science, Data Science, Statistics,

📌 Data Science Executive (India)
🏢 Taplend India
📍 India