Principal Data Scientist

Universal Ads, a part of Comcast, enables any brand, of any size, to seamlessly make and buy commercials across premium video reaching new qualified audiences at scale. Universal Ads combines premium and brand-safe video content directly from the most influential media companies with the ease and familiarity of social ad buying. It is your one-stop shop for high-quality video ads delivering performance and unmatched scale.

Job Summary

We’re looking for an experienced Data Scientist to join the Universal Ads team as our first dedicated data science hire. This role will help shape the foundation of Universal Ads’ measurement, attribution, targeting, and optimization systems, defining how advertisers understand and improve performance across premium video. You’ll work cross-functionally with Product, Engineering, and Data teams to design experiments and methodologies that power Universal Ads performance engine.

Job Description

Key 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 products 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.

• Provides consultative direction for use of analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools and machine learning techniques and statistics (e.g., predictive models, lifetime value, propensity models).

• Researches, educates and applies knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.

• Leads the development of customer centric models and optimization tools to support large scale projects that utilize online and offline data, structured and unstructured data, set top box data and media/behavioral/attitudinal data.

• Consistent exercise of independent judgment and discretion in matters of significance.

Minimum Qualifications 

• 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 st