Machine Learning + Predictive Model ( Mumbai)

PwC India; Mumbai, Navi Mumbai; Hybrid; INR 4,500,000 - 7,000,000; Full time

Benefits offered by this job

Leadership role

Impact on products and risk strategies

Exposure to cloud analytics tools

Job summary

PwC India invites a Lead Machine Learning Engineer to drive predictive analytics in the Financial Services domain from Mumbai. You will design and deploy production-grade models for credit risk, fraud, churn, and portfolio optimization, bridging data science with business strategy.

You will mentor junior data scientists, collaborate with stakeholders, and ensure governance and scalability with MLOps, cloud platforms, and robust monitoring in a fast-paced FS analytics hub.

Qualifications

• 5–10 years of Predictive Analytics experience in Financial Services.
• Experience with credit risk scoring, churn, CLV, or fraud models is preferred.
• Strong SQL skills and experience with Spark/PySpark for large-scale data.
• Familiarity with model governance, interpretability (SHAP/LIME), and bias mitigation.

Responsibilities

• Lead design, development and deployment of predictive models (Regression, Time-series, RF, XGBoost).
• Apply ML to FS problems like Credit Risk, CLV, Attrition, or Claims Propensity.
• Architect robust feature pipelines from diverse financial sources.
• Ensure models meet regulatory standards and interpretability requirements.
• Mentor and guide junior data scientists and collaborate with stakeholders.
• Work with MLOps to deploy models in high-availability environments.

Skills

Mentorship

Stakeholder collaboration

Problem solving

Education

Master's or PhD in Statistics / Mathematics / CS / Economics

Tools

Python

R

Scikit-learn

XGBoost

LightGBM

TensorFlow

PyTorch

Spark/PySpark

AWS SageMaker

Azure ML

Google Vertex AI

SHAP/LIME

Job description

Domain:Financial Services (Banking, Insurance, or Asset Management)

Role Overview

As aLead 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 asCredit 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 oninterpretability (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 theFinancial Servicessector.
• Tech Stack: Languages:Expert-levelPythonorR.
• 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.

Preferred Qualifications

• Experience dealing withimbalanced datasets(common in fraud and default prediction).
• Understanding of financial regulations (e.g., IFRS 9, Basel III) and their impact on data modeling.
• Masters or PhD in Statistics, Mathematics, Computer Science, or Economics.

What We Offer

• A leadership role in a fast-paced FS analytics hub in Mumbai.
• Direct impact on revenue-generating products and risk-mitigation strategies.
• Exposure to cutting-edge AI/ML tooling and cloud infrastructure.