Data Scientist - Outsourcing

Overview

We are seeking a skilled and intellectually curious Data Scientist with practical experience applying statistical, analytical, and machine learning methods to solve real‑world problems. This role requires strong technical foundations in applied statistics, predictive modeling, and data science workflows, along with the ability to translate complex findings into insights that drive business and operational decision‑making. Ideal candidates will have experience working with modern analytics tools and cloud platforms and may include recently matriculated Bachelor’s or Master’s degree candidates with meaningful hands‑on project, internship, or applied academic experience.

Note: Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity.

The Role

Key Responsibilities

• 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.

The Requirements

Required Qualifications:

• 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 Qualifications:

• 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.

Key Attributes for Success:

• Strong analytical curiosity and a passion for solving complex data problems.
• Ability to work independently on technical tasks while contributing effectively to cross‑functional teams.
• Excellent communication skills, especially when translating statistical findings into practical business insights.
• A disciplined, detail‑oriented approach to data quality and model integrity.

• Comfort working in environments that blend analytics, operations, cloud technology, and client‑facing collaboration.

   

This position will remain posted for a minimum of three business days from the date posted or until sufficient/appropriate candidate slate has been identified.

Compensation and Benefits

Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that base salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation.

Company Benefits

WTW provides a competitive benefit package which includes the following (eligibility requirements apply):

• 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). 

Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records.

At WTW, we trust you to know your work and the people, tools and environment you need to be successful. The majority of our colleagues work in a ”hybrid” style, with a mix of remote, in-person and in-office interactions dependent on the needs of the team, role and clients. Our flexibility is rooted in trust and “hybrid” is not a one-size-fits-all solution.

We understand flexibility is key to supporting an inclusive and diverse workforce and so we encourage requests for all types of flexible working as well as location-based arrangements. Please speak to your recruiter to discuss more.

EOE, including disability/vets