Back
Known brand, hybrid, metro data role with low experience preference and broad skillset drives high candidate density.
Credit-risk domain knowledge is preferred but core data science skills are reasonably transferable across industries.
Requires specific technical skills and degree but lacks firm years requirement, so moderate filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Support development of credit risk management and business intelligence analytic solutions for TransUnion’s clients across industries including credit card issuers, lenders, and banks.
Design and write programs for data extraction, segmentation, and statistical analysis on large datasets using languages such as R, Python, SQL, Hive, and Spark on cloud and server platforms.
Deliver analytic insights and recommendations through presentations to internal and external customers, including executive audiences, driving adoption of TransUnion’s analytic products and services.
Bachelor’s degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or another highly quantitative field.
Proficiency in R programming language; experience with SQL, Hive, Pig, Python, C/C++, or Java preferred.
Work Experience Required: At least 6 months of professional experience or internships in analytic roles within Financial Services or related industries preferred, but not strictly mandated.
Ability to travel 10-20%; hybrid work option requiring in-person presence at least two days per week.
Experienced in credit bureau data and credit risk analytics within Financial Services or related sectors.
Comfortable operating under modest supervision in a complex, dynamic, matrixed environment with cross-functional teams.
Skilled in handling large data sets using big data frameworks (Hadoop, Spark, cloud) and creating actionable analytic solutions that support business initiatives.