Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
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
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