Senior Data Scientist - AI and Machine Learning

IN-Senior Associate_ Data Scientist (AI/ML) __ Data & Analytics _ Advisory _Mumbai

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & Summary

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 optimise business performance and enhance competitive advantage.*Why PWCAt PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "

Job Description & Summary – Senior Associate_ Data Scientist_Advisory _ Mumbai 

 

Role Overview 

We are looking for a BFSI Machine Learning professional with strong hands-on experience in risk, fraud, underwriting, collections, and cross-sell modeling, along with exposure to GenAI / LLM-based use cases. The role involves end-to-end model development, client interaction, and delivery ownership across large banking and insurance engagements. 

 

Responsibilities 

Core ML & Analytics (BFSI) 

• Develop and deploy predictive and scorecard models, including: 

• Cross-sell / up-sell propensity models 

• Probability of Default (PD), LGD, EAD models 

• Collections prioritization and recovery models 

• Insurance underwriting scorecards 

• Claims fraud detection and leakage analytics 

• Apply ML/statistical techniques such as Logistic Regression, GBM/XGBoost, Random Forest, Neural Networks. 

• Perform feature engineering using transactional, bureau, behavioral, and alternate data. 

• Conduct model validation and stability monitoring (Gini, KS, PSI, CSI, lift, decile analysis). 

 

GenAI / LLM Exposure 

• Contribute to LLM-enabled BFSI solutions, including: 

• Automated credit / underwriting note generation 

• Claims investigation summaries 

• Risk and audit insight extraction 

• Hands-on experience with prompt engineering, embeddings, and RAG-based architectures. 

• Exposure to Azure OpenAI, OpenAI API, AWS Bedrock, or open-source LLMs. 

 

Cloud & Engineering 

• Strong hands-on coding in Python (pandas, numpy, sklearn, xgboost, SHAP). 

• Experience on at least one cloud platform: 

• AWS (SageMaker, S3, Glue) 

• Azure (Azure ML, Azure OpenAI, Data Factory) 

• GCP (Vertex AI) 

• Exposure to model deployment, monitoring, and MLOps pipelines is a plus. 

 

Client & Stakeholder Interaction 

• Work closely with client business, risk, fraud, and underwriting teams. 

• Translate business requirements into ML problem statements and solution designs. 

• Support client presentations, model documentation, and insights storytelling. 

• Mentor junior analysts and ensure delivery quality. 

 

Must-Have Skills 

• 5–10 years of experience in BFSI analytics / machine learning. 

• Hands-on experience in credit risk, fraud, underwriting, collections, or cross-sell modeling. 

• Advanced proficiency in Python. 

• Working knowledge of LLMs, GenAI, and prompt engineering. 

• Experience with cloud-based ML platforms. 

• Strong communication and stakeholder management skills. 

 

Good-to-Have 

• Experience in Big-4 / Tier-1 consulting / captive BFSI analytics teams. 

• Familiarity with model governance, explainability, and regulatory expectations. 

• Exposure to Graph ML, alternate data, or agentic AI frameworks. 

• Prior experience in client-facing analytics transformation programs. 

 

Mandatory skill sets: 

 

ML/GenAI/LLM/BFSI  

Preferred skill sets: 

 

ML/GenAI/LLM/BFSI  

Years of experience required: 

 

5—12 Years  

Education qualification: 

 

B.E.(B.Tech)/M.E/M.Tech 

 

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Bachelor of Engineering, Master of EngineeringDegrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Datasets

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Applied Macroeconomics, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Communication, Competitive Advantage, Continuous Process Improvement, Creativity, Data Analysis and Interpretation, Data Architecture, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Embracing Change, Emotional Regulation, Empathy, Geopolitical Forecasting {+ 24 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

Experience Level

Senior Level