Hiring for:
An exciting InsurTech startup building an AI-native stack for the Insurance.

Role:
Data Scientist – Risk & Fraud Modeling (3–5 Years) - Hand on Coding - Mumbai

Positions:
1

Experience:
3 to 6 years

Location(s):
Mumbai

Type:
On-site / Permanent

Salary:
Up to INR 35 LPA (based on fitment)

About the role

We are looking for a Data Scientist who combines deep BFSI domain expertise with solid machine learning and analytics capabilities. The ideal candidate has extensive experience in fraud, risk, underwriting, and decisioning models, and is excited about applying AI agents and agentic workflows to transform how insurers make decisions. This role will work closely with product, engineering, and customers to build next-generation AI-powered solutions for underwriting, claims, fraud detection, risk assessment, and operational automation.

Key Responsibilities

Data Science & Machine Learning

• Work on end-to-end lifecycle of machine learning and advanced analytics initiatives.

• Design, develop, validate,



and deploy predictive and prescriptive models for BFSI and insurance use cases.

• Build scalable data science solutions leveraging structured and unstructured data.

• Model monitoring, performance tracking, explainability, and governance practices.

• Establish best practices for experimentation, feature engineering, model evaluation, and MLOps. Fraud & Risk Analytics

• Design and enhance fraud detection and fraud prevention models.

• Build risk scoring, propensity, anomaly detection, and behavioral analytics models.

• Develop decisioning frameworks for underwriting, claims, collections, and customer risk assessment.

• Partner with business stakeholders to translate risk and fraud strategies into analytical solutions.

• Continuously improve model effectiveness while balancing customer experience and operational efficiency. AI & Agentic Decisioning

• Explore and implement AI agent architectures that assist or automate business decision-making.

📌 Data Scientist – Risk (Mumbai)
🏢 datavruti
📍 Mumbai