IN_ Senior Associate_ML Predictive Analytics_D&A_Advisory_Mumbai

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decision-making for clients. You will develop and implement innovative solutions to optimize business performance and enhance competitive advantage. Job Position Title: IN_ Senior Associate_ML Predictive Analytics_D&A_Advisory_Mumbai Responsibilities: · 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. · ML Frameworks: Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. · Data Handling: Advanced SQL and experience with Spark/PySpark for large-scale financial datasets. · Cloud & MLOps: Experience with AWS SageMaker, Azure ML, or Google Vertex AI. · Mathematics: Strong foundation in statistics, probability, and linear algebra as applied to financial forecasting. Mandatory skill sets: ML/Predictive Analytics/BFSI Preferred skill sets: ML/Predictive Analytics/BFSI Years of experience required: 3-6 Years Education qualification: B.E/B.Tech/MBA/M.E/M.Tech

• Experience: 3+ years
• Seniority: Mid Level
• Education: Bachelor's degree preferred
• Languages: English