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Mid-level ML role, strong brand, metro location, and broad cloud/ML requirements create high candidate competition.
Role demands credit-risk, bureau data and domain knowledge, reducing cross-industry transferability.
Explicit degree-and-years plus mandatory ML, deployment, Spark, and credit-risk expertise makes shortlisting highly strict.
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Lead development and deployment of analytic solutions across credit, fraud, insurance, and marketing applications, managing projects end-to-end.
Provide strategic consulting and analytic perspective to internal and external stakeholders, supporting business initiatives and adoption of analytic products.
Oversee and mentor small teams, drive innovation labs, and improve analytic processes using R, Python, and cloud-based big data technologies.
Master’s or PhD in quantitative field with 5+ years relevant experience OR Bachelor’s in quantitative field with 8+ years experience.
Experience in machine learning and deep learning developments with knowledge or exposure to Generative AI and NLP (LLMs, agentic applications).
Hands-on experience with cloud platforms (GCP/AWS), big data (Spark ML, PySpark), and end-to-end model deployment lifecycle.
Work Experience Required: 5+ years (Master’s/PhD) or 8+ years (Bachelor’s) in relevant fields; Location: hybrid with minimum 2 days/week onsite at assigned TransUnion office.
Experienced in financial services risk management and credit risk modeling lifecycle, familiar with credit bureau data and analytic products.
Capable of leading complex, cross-functional projects in fast-paced matrix organizations with strong stakeholder management and communication skills.
Strong technical leadership with a focus on scalable analytics solutions, process improvements, and mentoring junior team members.