As a Senior Data Science Leader in our consumer lending business, you will be responsible for owning the strategy, roadmap, and delivery of machine-learning and statistical models. Your role will involve developing credit risk models for underwriting and portfolio risk decisioning, as well as overseeing models for fraud risk, marketing response and propensity, customer lifecycle management, collections prioritization, account management, and pricing, line, and offer optimization. You will be a hands-on leader setting analytical standards, building well-documented models, mentoring a team of data scientists and ML practitioners, and collaborating with credit, fraud, marketing, and collections leaders.**Key Responsibilities:**- Own the model development strategy and roadmap across various consumer lending decisioning use cases.- Lead, hire, coach, and grow a team of data scientists and ML practitioners.- Direct the end-to-end model lifecycle including problem framing, data engineering, model development, and deployment.- Drive feature engineering and evaluate alternative data sources.- Establish and govern champion/challenger experimentation frameworks.- Own model monitoring for performance, drift, and stability.- Partner with model risk management and governance for validation and audit support.- Embed fair lending and regulatory awareness into model design.- Translate model outputs into actionable business strategies.- Communicate model strategy and results to executives and cross-functional partners.- Set and uphold analytical standards and reproducibility practices.**Qualifications:**- 10 years of experience in data science, statistical modeling,



or credit risk analytics.- 3 years of experience leading and developing data science or ML teams.- Deep expertise in building credit risk and portfolio decisioning models.- Robust hands-on Python and SQL skills.- Experience across the full model lifecycle.- Consumer lending or financial services experience.- Excellent communication skills.- Bachelors degree in a quantitative field.Preferred Qualifications:- Consumer lending experience with US consumer lending regulations knowledge.- Experience building models across multiple domains.- Hands-on experience with alternative data and real-time decisioning platforms.- Familiarity with explainability methods and fair-lending testing.- Experience upgrading a data science function.(Note: Additional details about the company were not provided in the job description.) As a Senior Data Science Leader in our consumer lending business, you will be responsible for owning the strategy, roadmap, and delivery of machine-learning and statistical models. Your role will involve developing credit risk models for underwriting and portfolio risk decisioning, as well as overseeing models for fraud risk, marketing response and propensity, customer lifecycle management, collections prioritization, account management, and pricing, line, and offer optimization. You will be a hands-on leader setting analytical standards, building well-documented models, mentoring a team of data scientists and ML practitioners, and collaborating with credit, fraud, marketing,



and collections leaders.**Key Responsibilities:**- Own the model development strategy and roadmap across various consumer lending decisioning use cases.- Lead, hire, coach, and grow a team of data scientists and ML practitioners.- Direct the end-to-end model lifecycle including problem framing, data engineering, model development, and deployment.- Drive feature engineering and evaluate alternative data sources.- Establish and govern champion/challenger experimentation frameworks.- Own model monitoring for performance, drift, and stability.- Partner with model risk management and governance for validation and audit support.- Embed fair lending and regulatory awareness into model design.- Translate model outputs into actionable business strategies.- Communicate model strategy and results to executives and cross-functional partners.- Set and uphold analytical standards and reproducibility practices.**Qualifications:**- 10 years of experience in data science, statistical modeling, or credit risk analytics.- 3 years of experience leading and developing data science or ML teams.- Deep expertise in building credit risk and portfolio decisioning models.- Strong hands-on Python and SQL skills.- Experience across the full model lifecycle.- Consumer lending or financial services experience.- Excellent communication skills.- Bachelors degree in a quantitative field.Preferred Qualifications:- Consumer lending experience with US consumer lending regulations knowledge.- Experience building models across multiple domains.- Hands-on experience with alternative data and real-time decisioning platforms.- Familiarity with explainability methods and fair-lending testing.- Experience upgrading a data science function.(Note: Additional details a

📌 Director - Data Science (India)
🏢 Applied Data Finance
📍 India