Machine Learning Platform Engineer

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Team Overview

This role is part of the Research & Development organization, focused on enabling and evolving enterprise data science capabilities. The team is responsible for protecting existing global data science environments, modernizing data science by onboarding practitioners to One True and cloud‑based tooling, and continuously enhancing data science and machine‑learning tools to be more automated, scalable, and user‑friendly. The team builds and improves the underlying platforms and tools that data scientists rely on every day, with strong involvement in innovation initiatives and customer‑facing use cases. This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Role Overview and Core Responsibilities

• Set requirements for Global Technology to support of the tools and frameworks used by analysts on distributed computing systems and participate in projects led by Global Technology as a subject matter expert on machine learning and scientific computing. 

• Provide oversight and hands-on support for the development of analytic solutions using languages such as R, Python, SQL, and Spark, formalizing some of these efforts into repeatable process improvements.  

• Lead new environment setup on behalf of data science teams. As a project leader, you will take ownership of all aspects of the project from environment design, to tool development, to training, and to global resource coordination. 

• Own data science requirements and tracking, working to identify strategies and opportunities to test and adopt TransUnion’s analytic products and services. In this capacity, you will interact directly with TransUnion’s matrix partners and provide an analytic perspective and general support as needed.  

• Contribute to research and innovation initiatives in collaboration with other DSA peers and may lead small analytic research teams or manage research interns on a project basis, as needed. 

• Participate in interviewing and evaluation of new talent, mentoring and training of junior colleagues, fostering a high-performance culture, and cultivating an environment that promotes excellence and reflects the TransUnion brand.  

Required Knowledge and Experiences

• Master’s or PhD degree in statistics, applied mathematics, financial mathematics, computer science, engineering, operations research, or other highly quantitative field; or a Bachelor’s degree in a quantitative field with at least five (5) years of relevant professional experience. In either case, the candidate will demonstrate a c