What We'll Bring

TransUnion, a leading risk information solutions company and one of the three major U.S. credit bureaus, is seeking interns to join various functions in TransUnion’s core analytical group. You will have the opportunity to apply your statistical modeling skills to help solve real problems for a variety of industries such as financial services and insurance.

The Data Science and Analytics team is an industry recognized, client-facing department that rewards an entrepreneurial spirit. We have deep technical expertise and an established reputation as an analytic solutions provider in the Financial Services and Insurance industries. We have a wealth of data and industry experience within our large group of highly-trained analysts, statisticians, engineers, and economists. We also have a modern computing environment based on best-in-class “big data” technologies and the freedom to explore new data sources and statistical methodologies. All of these resources will enable you to help us deliver next-generation analytic solutions for our customers.

Our Summer Internship Program will allow you to use & develop the skills you've learned in school while participating in engaging events such as: career development workshops, networking events, and guest speakers throughout this paid 12-week internship beginning in May or June 2022, depending on academic calendar.

During the COVID-19 pandemic, TransUnion has several safety protocols in place to protect associates, customers, and visitors. You may be required to be fully vaccinated against COVID-19 as a condition of employment and/or to participate in certain work-related activities. Exemption is available to qualified candidates as a reasonable accommodation. 

What You'll Bring

Currently enrolled in a undergraduate or graduate program in statistics, mathematics, engineering, operations research, economics, or a related quantitative field.

Advanced programming skills in one or more statistical languages, such as R, Python.

Proficient with Microsoft Excel, and Microsoft PowerPoint.

Strong analytical, critical thinking & creative problem solving skills.

Ability to conduct meaningful research with a high degree of independence.

Familiar with relational databases and “Big Data” technologies.

Able to communicate effectively at multiple levels within the organization, both verbally and in writing.

We’d love to see: 

Demonstrated interest in applications of analytic methods in the financial services and insurance industries. 

Impact You'll Make

This position will conduct a research project independently or as part of a team, under the supervision of a senior member of the Data Science & Analytics team. The project scope will be designed to be achievable within the expected duration and total number of hours of the internship. At the conclusion of the project, the supervisor will conduct an assessment of the quality, completeness, and usefulness of the work. Executing the project will provide the incumbent with the opportunity to gain practical knowledge of analytic applications in industries utilizing consumer credit data, including potentially having direct participation in actual customer projects.

Review the proposed research topic and generate a problem-solving methodology in collaboration with the supervisor. The proposed methodology should either demonstrate a technique not commonly used by the department or a substantial process improvement to a commonly used method. 

Independently manage the chosen project and provide the supervisor with periodic progress reports. 

Design an appropriate testing environment to measure applicability of the proposed methodology to the needs of the business unit and compare with alternative approaches, as appropriate. 

Create any software code necessary to produce findings. 

Carefully document all sources and research findings. Prepare a summary of findings in an internal white paper for senior management. 

Present summary of findings to research sponsors. Conduct training for other Associates as appropriate. 

Provide support for Data Science & Analytics projects beyond the scope of the research project, as needs arise.