Data Scientist

Role Summary

We are seeking a Senior Data Scientist (6–7 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, CatBoost, LightGBM 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 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 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, CatBoost, LightGBM)

· 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), BigQuery 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