Hybrid Data Scientist

at EXL

• Job title: Data Scientist
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: BigQuery, Cloud, Google Cloud Platform, Python, SQL
• Location requirements: Hybrid, Gurugram, India

About the role

• Senior Data Scientist developing fraud detection models for insurance claims utilizing statistical analysis and machine learning techniques. Collaborating with stakeholders and managing deliverables to drive insights.

Responsibilities

• Develop and deploy fraud detection models for 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

Requirements

• 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)
• 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
• 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