WTW is seeking a skilled and intellectually curious Data Scientist to apply statistical, analytical, and machine learning methods to solve real-world problems. The role involves building data pipelines, constructing visualizations, and collaborating with cross-functional teams to drive business insights and operational improvements.
Apply advanced descriptive and inferential statistical methods to explore data, evaluate hypotheses, and produce actionable insights
Build, optimize, and interpret regression models (linear, logistic), and classification models commonly used in data science, including tree‑based and ensemble methods
Develop robust data pipelines and analytic workflows using R or Python, including data ingestion, cleaning, feature engineering, and model deployment support
Construct high‑quality data visualizations, dashboards, and analytic stories that clearly communicate trends, relationships, and operational insights to diverse audiences
Write and optimize SQL queries for data extraction, transformation, and validation across relational data environments
Implement analytics solutions within cloud environments, such as Azure services, Azure Foundry, Blob Storage, and SharePoint, to support scalable data storage, processing, and reporting
Build and maintain analytical assets and reusable code to streamline recurring analyses and enhance data science capability
Partner with product, operational, and technology teams as an informed contributor in Agile development environments, applying concepts such as MVP thinking, user stories, iterative feedback cycles, and release planning
Engage with operational stakeholders—including client delivery, service center operations, and benefits administration teams—to provide data‑driven perspectives that support performance improvement, quality management, and client outcomes
Communicate modeling approaches, assumptions, risks, and results in a clear and credible manner to both technical and non‑technical audiences
Qualification
Required
Bachelor's or Master's degree in Statistics, Data Science, Mathematics, or a related quantitative field
Demonstrated hands‑on experience with:
+ Applied statistics and exploratory data analysis
+ Regression modeling (linear and logistic)
+ Classification models and model evaluation techniques
+ R and/or Python, including key data science libraries
+ SQL, including intermediate query development
+ Data visualization tools or libraries (e.g., Power BI, Tableau, ggplot2)
Working familiarity with cloud analytics environments, file storage systems, and enterprise data access methods
Experience preparing and analyzing structured and unstructured datasets, with strong data‑wrangling capabilities
Ability to diagnose model performance issues, such as class imbalance, overfitting, feature interactions, and data quality constraints
Preferred
Exposure to operations‑heavy environments such as benefits administration, service center operations, or outsourcing workflows
Understanding of operational and service metrics, including AHT, FCR, SLAs, CSAT, and related KPIs
Experience participating in Agile product development processes
Familiarity with visualization and BI tools used to deliver insights at scale
Benefits
Health and Welfare Benefits: Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program)
Leave Benefits: Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off (Washington State only)
Retirement Benefits: Contributory Pension Plan and Savings Plan (401k).
WTW is a global advisory and solutions company that helps clients around the world turn risk into a path for growth.
