Job Details:

Position                :                 Senior Data Scientist – Insurance Analytics

Experience           :                 3-10 Years

Location               :                 Gurgaon(Primary)/Noida/Bangalore/Pune/Remote

Shift                       :                 1:30PM to 11:30PM (10 Hours Shift. Also depends on the project/work dependencies)

Job Title: Senior Data Scientist – Insurance Analytics

Role Overview

We are seeking a Senior Data Scientist (3–10 years of experience) to support an analytics initiative focused on the insurance domain. This is a client facing role requiring strong analytical expertise, hands-on modeling experience and the ability to independently drive analysis, present insights and collaborate with stakeholders.

The ideal candidate will have a solid foundation in statistical modeling and hypothesis testing, deep experience in tree-based and ensemble machine learning models, exposure to cloud-based data platforms and working knowledge of modern Generative AI and Large Language Model (LLM) techniques relevant to insurance analytics

Key Responsibilities

• Perform exploratory data analysis (EDA), feature engineering, and hypothesis testing to identify fraud patterns and anomalies.

• Build, evaluate, and optimize traditional statistical models as well as tree-based ML models such as Random Forest, XGBoost, CatBoost, and LightGBM.

• Explore and apply LLM based approaches (e.g. text classification, summarization, entity extraction) for leveraging unstructured data such as claim notes, adjuster comments and documents.

• Develop GenAI powered accelerators for documentation, feature ideation, data enrichment and model insight generation.

• Independently conduct data analysis, research, model experimentation and translate findings into actionable insights.

• Write clean, efficient and production ready code using Python and SQL.

• Work extensively with large datasets using cloud platforms, primarily Google Cloud Platform (GCP).

• Query and manage data using Big Query and datasets stored in Cloud Storage (Buckets).

• Use Git for version control, collaboration and code review.

• Prepare clear, concise and impactful presentations for clients, explaining analytical findings to both technical and nontechnical stakeholders.

• Collaborate with business, data engineering, and client teams to ensure models align with investigation strategies and broader business objectives

Required Skills & Qualifications

• 7–8 years of hands on experience in data science, analytics, or applied machine learning

• Strong understanding of statistical modeling, probability concepts, and hypothesis testing

• Proven experience with tree-based and ensemble machine learning models (RF, XGBoost, CatBoost, LightGBM)

• Experience working with unstructured data and NLP techniques, preferably including LLMs (OpenAI, Gemini, Llama, etc.)

• Practical exposure to GenAI workflows such as prompt engineering, fine tuning, retrieval augmented generation (RAG), or automated insight generation

• Expert‑level SQL for data extraction, transformation, and analysis

• Strong Python skills for data analysis, machine learning, and LLM based pipelines

• Experience using Git for source code management

• Solid exposure to cloud based analytics environments, preferably Google Cloud Platform (GCP), Big Query, and Cloud Storage

• Ability to work independently, manage deliverables and drive tasks end to end.

• Excellent verbal and written communication skills, essential for a client facing role.

Candidate Profile

• Bachelor’s/Master’s degree in economics, statistics, mathematics, computer science/engineering, operations research, or related analytics areas.

• Strong data analysis experience with complex, real world datasets.

• Demonstrated capability in solving business problems using both traditional ML and emerging GenAI/LLM based approaches.

• Superior analytical thinking and problem-solving skills.

• Outstanding written and verbal communication skills with confidence in client interactions.