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Strong brand, metro location, mid-senior ML generalist, and broad required skills raise applicant competition.
Core ML skills transfer across industries but credit-risk and bureau-data familiarity increases role specificity.
Explicit degree-plus-years requirement and mandatory ML/cloud/Spark experience make shortlisting stringent.
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Lead development and deployment of analytic solutions across credit risk, fraud, insurance, and marketing domains.
Manage end-to-end analytic projects including opportunity management, solution design, development, deployment, and ongoing monitoring.
Provide strategic consultation and analytic oversight to internal and external stakeholders, including mentoring junior team members and leading small research teams.
Master's or PhD in quantitative fields with at least 5 years relevant experience OR Bachelor's in quantitative fields with at least 8 years relevant experience.
Experience in Machine Learning & Deep Learning development; exposure to GenAI and NLP is a plus.
Experience with cloud platforms (GCP/AWS) handling large datasets in distributed environments and end-to-end model deployment lifecycle including Spark ML and Pyspark.
Hybrid work location requirement: at least two days per week in-person at a TransUnion office.
Proven track record leading complex analytic projects in financial services risk management, especially credit risk modeling.
Experienced in cross-functional stakeholder engagement in fast-paced, matrixed organizations with strong business acumen.
Capable of managing multiple projects simultaneously with limited supervision while driving innovation and best practices in data science analytics.