Data Scientist - Insurance Analytics

PwC; Mumbai; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A leading consulting firm in Mumbai is seeking a skilled Data Scientist for Insurance Analytics. The ideal candidate will have 4–7 years of experience, with hands-on expertise in machine learning, data science, and analytics specific to the insurance domain. Responsibilities include developing predictive models, conducting exploratory data analysis, and collaborating with teams to enhance data-driven insights. Strong proficiency in Python and SQL is essential, along with good communication skills. Competitive salary and relocation assistance may be offered.

Qualifications

• 4–7 years of experience in Data Science.
• Hands-on experience in machine learning model development.
• Mandatory insurance domain experience (minimum 3 years).

Responsibilities

• Build and implement predictive models for insurance use cases.
• Perform data extraction, preprocessing, and exploratory data analysis.
• Apply machine learning techniques and evaluate model performance.
• Collaborate with cross-functional teams for analytics and model lifecycle.

Skills

Machine learning

Data Science

Analytics

Insurance Analytics

Python

SQL

Statistical concepts

Communication skills

Tools

Databricks

AWS

Azure

Power BI

Tableau

Job description

🖊️ PwC India is actively looking for talented candidates those who will be at Mumbai location and also willing to relocate candidates!! 📜

Interested candidates please fill below form:

https://lnkd.in/dicwXKmn

Please Send your resume to [e-mail]

Please mention subject line as Insurance Analytics Consultant

Job Description – Data Scientist - Insurance Analytics

Location: Mumbai (only)

Experience: 4–7 years

Mandatory Skills: Machine learning, Data Science, Analytics, Insurance Analytics

Role Overview

PwC India is looking for Data Scientists with strong insurance domain expertise to work on advanced analytics and machine learning use cases across underwriting, claims, fraud, and customer analytics. The role requires hands‑on experience in model development, data analysis, and solving business problems using data‑driven approaches.

Key Responsibilities

• Build and implement predictive models for insurance use cases such as claims, fraud, persistency, and risk analytics
• Perform data extraction, preprocessing, and exploratory data analysis (EDA) on large datasets
• Apply appropriate machine learning techniques and evaluate model performance using relevant metrics
• Perform feature engineering leveraging both data insights and insurance domain knowledge
• Translate business problems into analytical and modeling frameworks
• Generate actionable insights and effectively communicate findings to stakeholders
• Develop dashboards or visualizations using Power BI / Tableau where required
• Collaborate with cross‑functional teams to support end‑to‑end analytics and model lifecycle

Must-Have Skills

• Hands‑on experience in machine learning model development
• Mandatory insurance domain experience (minimum 3 years)
• Proficiency in Python and SQL
• Experience in EDA, feature engineering, and model evaluation
• Strong understanding of statistical and machine learning concepts
• Experience working with Databricks / AWS / Azure environments
• Good communication and stakeholder management skills

Preferred

• Exposure to GenAI / LLMs / Agentic AI use cases
• Understanding of model deployment or MLFlow MLOps workflows