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Known global brand, metro location, and generalist data-science role increase applicant competition.
Credit risk and bureau-data expertise makes industry experience highly relevant and less transferable.
Mandatory programming, statistical, and credit-data skills increase screening rigor despite no strict years requirement.
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Support development of credit risk management and business intelligence analytic solutions through consulting and research for TransUnion clients.
Partner with cross-functional teams to develop predictive risk management solutions and drive business initiatives globally for various lending sectors.
Design and write programs for data extraction, segmentation, and statistical analysis on large datasets using languages like R, Python, SQL, Hive, and Spark; deliver analytic insights to diverse stakeholders.
Bachelor's degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or a related quantitative field.
Proficiency in statistical programming (preferably R) and familiarity with data manipulation languages such as SQL, Hive, Python, or Java.
Ability to travel 10-20%; hybrid work requires minimum two days per week onsite at assigned TransUnion office.
Work Experience Required: Minimum 6 months of professional or internship analytic experience in financial services or related industries preferred; not strictly mandatory.
Experienced in developing credit risk and business intelligence solutions within financial services or related domains, including familiarity with credit bureau data.
Capable of operating with modest supervision in a complex matrixed environment and managing multiple assignments with strong project management skills.
Technically adept with modern big data tools and environments (Hadoop, Spark, cloud platforms) and experienced in data visualization tools like Tableau.