Senior Data Scientist - AI and Machine Learning

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