Data Scientist; Machine learning - XG boost

Position: Data Scientist (Machine learning - XG boost) (Multiple locations)
Location: Bengaluru

Senior Data Scientist – Machine Learning (Traditional Models)
Experience - 6 to 10 years
Location -  Bangalore/Noida/Gurugram/Pune

Fraud Analytics (LTC Claims)
Role Summary
We are seeking a  Senior Data Scientist (6–10 years of experience)  to support a  fraud analytics initiative focused on Long‑Term Care (LTC) insurance claims . 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 , combined with deep rooted experience in  tree‑based and ensemble machine learning models , and cloud‑based data platforms.

Key Responsibilities
Develop and deploy  fraud detection models  for LTC insurance claims using statistical and machine learning techniques
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 models  such as Random Forest, XGBoost, Cat Boost, Light

GBM etc.
Independently conduct  data analysis, research, and 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 handle 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 non‑technical stakeholders
Collaborate with business, data engineering, and client teams to ensure models align with fraud investigation and business objectives

Required Skills & Experience
6–7 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, Cat Boost, Light

GBM)
Expert‑level SQL  for data extraction, transformation, and analysis
Strong Python skills  for data analysis and modeling
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
Superior  analytical thinking and problem‑solving skills
Outstanding  written and verbal communication skills , with confidence in client interactions