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 (610 years of experience) to support a fraud analytics initiative focused on LongTerm Care (LTC) insurance claims. This is a clientfacing role requiring strong analytical expertise, handson 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 treebased and ensemble machine learning models, and cloudbased 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 treebased models such as Random Forest, XGBoost, CatBoost, LightGBM etc.
- Independently conduct data analysis, research, and model experimentation, and translate findings into actionable insights
- Write clean, efficient, and productionready code using Python and SQL
- Work extensively with large datasets using cloud platforms, primarily Google Cloud Platform (GCP)
- Query and manage data using BigQuery, 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 nontechnical stakeholders
- Collaborate with business, data engineering, and client teams to ensure models align with fraud investigation and business objectives
Required Skills & Experience
- 67 years of handson experience in data science, analytics, or applied machine learning
- Strong understanding of statistical modeling, probability concepts and hypothesis testing
- Proven experience with treebased and ensemble machine learning models (RF, XGBoost, CatBoost, LightGBM)
- Expertlevel 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 cloudbased analytics environments, preferably Google Cloud Platform (GCP), BigQuery and Cloud Storage
- Ability to work independently, manage deliverables, and drive tasks endtoend
- Excellent verbal and written communication skills, essential for a clientfacing 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, realworld datasets
- Superior analytical thinking and problemsolving skills
- Outstanding written and verbal communication skills, with confidence in client interactions
