All fields marked * are required
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.
Required
Preferred
All fields marked * are required
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.
Required
Preferred