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Popular mid-level ML role in a metro with broad cloud, deployment, and Spark skill requirements.
Core ML and data skills are transferable, but credit-risk and bureau expertise increases domain specificity.
Explicit degree and years requirements plus mandatory ML, deployment, cloud and Spark skills.
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Lead development and deployment of analytic solutions across credit, fraud, insurance, and marketing business domains.
Manage and execute complex custom analytic projects end-to-end including proposal writing, solution design, development, deployment, and ongoing monitoring.
Oversee and mentor a small analytic team, provide client-facing consulting, and drive innovation initiatives including research labs and process improvements.
Master’s or PhD in quantitative field with minimum 5 years relevant experience, OR Bachelor’s with minimum 8 years relevant experience.
Hands-on experience in Machine Learning, Deep Learning, and end-to-end model deployment lifecycle.
Familiarity with cloud platforms (GCP/AWS) and distributed computing environments, Spark ML, and Pyspark ecosystem.
Work Location: Hybrid with minimum two days per week at assigned TransUnion office.
Experienced in credit risk modeling and financial services risk management, with understanding of credit bureau data and solutions.
Proven ability to manage multiple complex analytics projects in fast-paced, collaborative environments with limited supervision.
Strong client engagement and stakeholder management skills, capable of translating technical concepts into actionable business recommendations.