& Summary–SeniorAssociate_DataScientist_Advisory_Mumbai

We are looking for a BFSI Machine Learning professional with strong hands-on experience in risk, fraud, underwriting, collections, and cross-sellmodeling, along with exposure to GenAI / LLM-based use cases The role involves end-to-end model development, client interaction, and deliveryownership 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-basedarchitectures

• 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, andMLOpspipelines 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, andinsightsstorytelling.

• 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

• Advancedproficiencyin 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 experiencerequired

5—12 Years

Education qualification:

B.E.(B.Tech)/M.E/M.Tech