About the job
Senior Data Scientist Insurance Domain (IMMEDIATE TO 20 DAYS JOINERS) Locations - Pune, Bangalore-Gurugram-Noida (Hybrid) Exp - 5- 10 Years Role Summary We are looking for a Senior Data Scientist (5-10 years of experience) with strong expertise in machine learning, statistical modeling, and insurance domain analytics. The role focuses on building fraud detection and risk analytics models for insurance claims, insurance claims datasets. This is a client-facing role, requiring the ability to independently conduct analysis, build predictive models, and translate analytical insights into business recommendations for stakeholders. Key Responsibilities Develop and deploy fraud detection and risk analytics models for insurance claims using statistical and machine learning techniques. Perform exploratory data analysis (EDA), feature engineering, and hypothesis testing to identify fraudulent claim patterns and anomalies. Design and implement machine learning models. Analyze large insurance claims datasets to detect abnormal patterns, suspicious transactions, and fraud indicators. Write efficient and scalable code using Python and SQL for data analysis, modeling, and automation. Work with large scale datasets on cloud platforms, preferably Google Cloud Platform (GCP). Query and analyze data using BigQuery, and manage datasets stored in Cloud Storage. Maintain version control and collaborative workflows using Git. Present analytical insights, model results, and fraud patterns to business stakeholders and clients through clear reports and presentations. Collaborate with data engineering, business teams, and fraud investigation units to align models with real-world insurance processes. Continuously improve model performance through experimentation, validation, and optimization techniques. Required Skills & Experience 6-8 years of experience in Data Science / Machine Learning / Advanced Analytics Experience in Insurance domain (Claims Analytics / Fraud Detection / Risk Analytics) Strong understanding of statistics, probability, and hypothesis testing Advanced SQL skills for large-scale data analysis Strong Python programming for machine learning and data analysis Experience with Git for version control Exposure to cloud analytics environments, preferably: Google Cloud Platform (GCP) BigQuery Cloud Storage Ability to work independently and manage end-to-end data science projects Excellent communication and stakeholder management skills Preferred Experience Experience working with insurance claims datasets (LTC / Health / Life / Property & Casualty) Experience presenting data insights to clients and business leaders Education Bachelors or Masters degree in: Statistics Mathematics Economics Computer Science / Engineering Operations Research Data Science or related analytical field
Requirements
- Machine Learning
- Statistical Modeling
- Python
- SQL
- Data Analysis
Qualifications
- Bachelors or Masters in Statistics
- Mathematics
- Economics
- Computer Science
- Engineering
- Operations Research
- Data Science
Preferred Technologies
- Machine Learning
- Statistical Modeling
- Python
- SQL
- Data Analysis
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