Description:
Job Description: Lead / Senior Machine Learning Engineer (Predictive Analytics) Location: Mumbai (On-site/Hybrid) Experience: 5 – 10 Years Notice Period: Immediate Joiners Preferred Domain: Financial Services (Banking, Insurance, or Asset Management) Role Overview As a Lead Machine Learning Engineer, you will bridge the gap between complex financial data and actionable business strategy. You won't just build models; you will design the predictive engines that power credit scoring, fraud detection, churn prediction, or portfolio optimization. We need a hands-on expert who understands the "why" behind the math and the "how" of production-grade deployment. Core Responsibilities · End-to-End ML Development: Lead the design, development, and deployment of predictive models (Regression, Time-series, Random Forests, XGBoost, etc.) tailored for FS use cases. · FS-Specific Analytics: Apply machine learning to solve domain-specific problems such as Credit Risk scoring, Customer Lifetime Value (CLV), Attrition Modeling, or Claims Propensity. · Feature Engineering: Architect robust feature pipelines from disparate financial sources (transactional logs, CRM data, market feeds). · Model Governance: Ensure all models meet FS regulatory standards, focusing on interpretability (SHAP/LIME) and bias mitigation. · Strategy & Mentorship: Guide junior data scientists and collaborate with stakeholders to translate business problems into technical roadmaps. · Productionalization: Work with MLOps to deploy models into high-availability environments, ensuring scalability and performance monitoring. Technical Requirements · Advanced Analytics: 5-10 years of experience in Predictive Analytics with a proven track record in the Financial Services sector. · Tech Stack: * Languages: Expert-level Python or R. o ML Frameworks: Scikit-learn, XGBoost, LightGBM, TensorFlo