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Team Overview
The Data Science and Analytics team drives advanced analytics and AI solutions to solve complex business problems and enable data-driven dThe Data Science and Analytics team develops advanced analytics and artificial intelligence solutions that address complex business problems and enable data-driven decision-making across TransUnion. The team translates business strategy into scalable analytics solutions that deliver measurable impact, partnering closely with Product, Engineering, and other business stakeholders. This role reports to the Director, Data Science and Analytics.
This is a remote position which may require occasional in-person attendance at work-related events at the discretion of management.
Role Overview And Core Responsibilities
Own end-to-end delivery of AI, data science, and analytics projects, from problem definition through deployment and continuous improvement, while managing priorities, quality, timelines, and measurable business impact.
Design, build, and maintain scalable data pipelines, machine learning models, and analytical solutions aligned with business strategy and stakeholder needs.
Lead analytics engagements using AI and descriptive, predictive, and prescriptive techniques across diverse business use cases.
Translate business objectives into actionable, data-driven roadmaps, define success metrics, and demonstrate the value of analytical solutions.
Collaborate with Product, Engineering, and business stakeholders to align priorities, manage dependencies, mitigate risks, and support timely delivery.
Communicate analytical insights, risks, and recommendations through executive-ready presentations, visualizations, and data storytelling.
Improve models, processes, and analytical workflows through automation, optimization, experimentation, and emerging technologies.
Mentor junior team members through code reviews, technical guidance, knowledge sharing, and analytical and engineering best practices.
Required Knowledge And Experiences
Master’s degree with 3+ years OR Bachelor’s degree with 5+ years in a quantitative field.
Demonstrated experience developing and deploying machine learning models across the full lifecycle, including problem formulation, model development, validation, deployment, monitoring, and improvement.
Demonstrated experience designing and implementing artificial intelligence solutions that address business needs and produce measurable outcomes.
Strong analytical, critical-thinking, and problem-solving capabilities, with experience translating complex data into practical business recommendations.
Experience independently managing analytical projects and communicating effectively with technical and non-technical stakeholders in collaborative, fast-paced environments.
Required Technical Skills
· Proficiency in Python or R for statistical analysis, modeling, and machine learning.
· Advanced proficiency in Structured Query Language (SQL) for data preparation, analysis, and validation.
· Experience with large-scale data processing frameworks, such as Apache Spark or Apache Hive.
· Experience designing scalable machine learning solutions, analytical data pipelines, and production-ready workflows.
· Working knowledge of data visualization, analytical storytelling, and cloud-based or big data ecosystems.
We’re also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we’re happy to support your career development and growth in:
· Experience applying analytics within fraud, identity, credit risk, or financial services environments.
· Experience using advanced analytical methods, such as machine learning, optimization, or simulation, to solve real-world business problems.
· Familiarity with Extract, Transform, and Load (ETL) frameworks and end-to-end data engineering workflows.
· Experience delivering client-facing or consulting-oriented analytics engagements.
· Ability to work independently in…