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Popular data-analyst role, metro location, and broad generalist skillset increase applicant competition.
Credit-risk domain knowledge helps, but core data science skills are broadly transferable across industries.
Quantitative degree and technical toolset strongly preferred, but years-of-experience not strictly mandated.
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Support development of credit risk management and business intelligence analytic solutions through consulting and research for TransUnion’s clients.
Develop predictive risk management and business intelligence solutions for financial services sectors such as credit card, auto, mortgage lenders, and collections agencies.
Design and write programs for data extraction, segmentation, and statistical analysis on large datasets using tools like R, Python, SQL, Hive, and Spark; deliver analytic insights and recommendations to internal and external stakeholders.
Bachelor’s degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or other highly quantitative field.
Proficiency in statistical programming languages such as R; experience with SQL, Python, Hive, Spark preferred.
Work Experience Required: At least 6 months of professional experience or internships performing analytic work in Financial Services or related industries preferred; not strictly mandatory.
Willingness to travel 10-20%; hybrid work model requiring minimum two days a week onsite at an assigned TransUnion office.
Experience with credit bureau data and credit risk business practices to support analytic solution development focused on credit risk management.
Ability to operate with modest supervision in a complex, dynamic, and matrixed environment involving multiple stakeholders.
Skills in data visualization tools such as Tableau and advanced Excel skills (formulas, macros, pivot tables) to create detailed analytical reports.