Early Careers: Data Analyst Internship

WTW•New York, NY

1d•$18 - $20

About The Position

The Data Analyst Intern will collect, clean, organize, and analyze data from internal and external sources. The role involves developing analytical models, producing dashboards and reports, and using statistical and quantitative methods to support business decisions. The intern will work with business and technical colleagues to translate requirements into analytical outputs and help improve the quality, efficiency, and automation of analysis and reporting. Candidates must be pursuing a Bachelor’s or Master’s degree and graduate between December 2027 and June 2029. Applicants must be authorized to work in the United States indefinitely without visa sponsorship. The position pays $18–$20 per hour and is eligible for overtime. WTW offers a competitive benefits package, including a contributory pension plan and 401(k) Savings Plan, subject to eligibility requirements.

Requirements

Bachelor’s or Master’s degree with a minimum overall GPA of 3.0.
Strong analytical and problem-solving skills, including the ability to interpret complex datasets.
Good working knowledge of Excel, including data manipulation and analytical modeling.
Experience with Python or a similar analytical or programming language.
Understanding of statistics, regression, forecasting, and other quantitative techniques.
Ability to visualize and communicate data effectively through reports and presentations.
Strong attention to detail and commitment to data quality.
Good written and verbal communication skills, including the ability to explain analytical findings to non-technical audiences.
Expected to graduate with a Bachelor’s or Master’s degree between December 2027 and June 2029.
Ability to work legally in the United States indefinitely without visa sponsorship.

Nice To Haves

Interest in financial, commercial, or business analysis.

Responsibilities

Collect, clean, organize, and analyze data from multiple internal and external sources.
Develop analytical models to identify trends, relationships, and key business drivers.
Create dashboards, reports, and presentations that communicate findings to stakeholders.
Support benchmarking, forecasting, and performance analysis.
Use statistical and quantitative techniques to answer business questions and inform decision-making.
Work with business and technical colleagues to understand requirements and translate them into analytical outputs.
Identify opportunities to improve the quality, efficiency, and automation of existing analysis and reporting.