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Recognized employer, popular data science role, unspecified experience, and metro location drive high competition.
Strong data science skills transferable, but credit-risk and bureau-data familiarity increases domain specificity.
Moderate technical and domain skill requirements but no strict years mandate.
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Develop and support credit risk management and business intelligence analytic solutions for TransUnion’s clients globally.
Design, code, and analyze large datasets using R, Python, SQL, Hive, and cloud-based big data frameworks to deliver predictive risk management models and insights.
Collaborate across internal and external teams to present analytic insights and drive adoption of TransUnion’s analytic products.
Bachelor’s degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or another highly quantitative field.
Strong programming proficiency in R; experience with Python, SQL, Hive, and big data tools preferred.
Work Experience Required: At least 6 months professional experience or internships in analytics related to Financial Services or similar domains.
Willingness and ability to travel 10-20%; hybrid work model requiring at least two days per week onsite.
Analytically skilled individual capable of working with large consumer lending datasets and developing predictive models for credit risk across consumer finance segments.
Experienced in programming statistical analyses and data manipulation in multi-language and big data environments, including cloud-based platforms.
Comfortable operating with modest supervision in a fast-paced, matrixed global organization and effectively communicating analytics to technical and executive stakeholders.