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, business driven problems. This is a client facing role that requires not only strong technical foundations in applied statistics and predictive modeling, but also the ability to clearly communicate insights to internal partners and external stakeholders.
The role supports client delivery and operational teams, translating complex data into actionable insights that inform decision making, performance improvement, and client outcomes. Ideal candidates will have experience working with modern analytics tools and cloud platforms and may include early career professionals or recently matriculated Bachelor’s or Master’s degree candidates with meaningful hands on project, internship, or applied academic experience.
Location Note: This role is open to remote candidates; however, there is a strong preference for individuals who are willing to be on site in Charlotte periodically. While not required, in-office presence a few times per month is highly beneficial, particularly for early career development, collaboration, and exposure to client facing work.
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 that support both internal teams and client needs.
- 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 support for model deployment.
- Construct high‑quality data visualizations, dashboards, and analytic narratives that clearly communicate trends, relationships, and operational insights to client‑facing and non‑technical 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 team‑wide data science capabilities.
- Partner with product, operational, and technology teams as an informed contributor in Agile development environments, applying MVP thinking, user stories, iterative feedback cycles, and release planning.
- Engage directly with operational and client‑aligned 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 clearly and credibly to both technical and non‑technical, client‑facing audiences.
Qualifications
Requirements
Required Qualifications
- 2–3 years of relevant professional experience, including 1–2+ years of office‑based, client‑facing, or client management experience (e.g., working with internal or external stakeholders, supporting client deliverables, or operating in a professional services environment).
- 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
- Willingness and ability to be on‑site in Charlotte periodically, particularly during onboarding and early tenure.
- Exposure to operations‑heavy or client‑service environments such as benefits administration, service center operations, consulting, 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 enterprise visualization and BI tools used to deliver insights at scale.
Key Attributes for Success
- Strong analytical curiosity and a passion for solving complex, real‑world data problems.
- Comfort working in client‑facing and stakeholder‑driven environments, balancing technical rigor with clear communication.
- Ability to work independently on technical tasks while contributing effectively to cross‑functional and client‑aligned teams.
- Excellent communication skills, especially when translating statistical findings into practical business and operational insights.
- A disciplined, detail‑oriented approach to data quality, model integrity, and professional delivery.
- Openness to learning through collaboration, in‑office engagement, and exposure to client‑facing work—especially valuable for early‑career growth.
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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.
Compensation
The base salary compensation range being offered for this role is $90,000-$125,000 USD per year.
This role is also eligible for an annual short-term incentive bonus.
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