Director of Data Science leading the Identity fraud product development at TransUnion. Collaborating with stakeholders to build market - leading identity data products and analytic solutions.
About the role
- Data Scientist shaping performance measurement and optimization for Universal Ads. Collaborating with Product, Engineering, and Data teams, focusing on large datasets and experimental analysis.
Responsibilities
- Experience navigating and working with large data sets, and designing and analyzing experiments
- Develop experimentation and causal inference frameworks to quantify the impact of new product s and advertiser-level performance ramps, including methods to address skewness and low-signal environments
- Analyze large-scale identity, auction, and conversion datasets to uncover performance drivers, optimize advertiser ROI, and inform measurement and optimization roadmap
- Support the development of advanced measurement methodologies ( e.g. Halo), collaborating closely with Product and Engineering to test, validate, and scale solutions
- Translate analytical insights into production-ready features and system improvements
- Stay current with advancements in data science, machine learning, and advertising technology, incorporating new methodologies and tools into the team’s workflow
- Conduct rigorous analyses and communicate findings clearly to technical stakeholders, driving data-informed decisions across teams
- Interacts and leads meetings with product and service teams to identify questions and issues for data analysis and experiments.
Requirements
- Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field
- 10+ years of experience in data science, analytics, or applied statistics (or 5+ years with Ph.D.)
- Proven ability to work with large, complex datasets
- Proficiency in Python, SQL or R and statistical/machine learning libraries
- Strong understanding of experiment design, causal inference, and modeling techniques (e.g., regression, uplift modeling, Bayesian methods)
- Experience with data visualization tools (e.g., Tableau, Looker, Plotly) and storytelling for non-technical audiences.
Benefits
- health insurance
- retirement plans
- paid time off
- flexible work arrangements
- professional development
- bonuses
- best-in-class Benefits
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