At T-Mobile, the business problem is to optimize marketing spend, measure media effectiveness, and drive business outcomes through the development of groundbreaking machine learning and AI-driven models.
Requirements
- Proven experience in marketing and media analytics, with a focus on attribution modeling, causal inference, and media mix optimization.
- Strong background in machine learning, econometrics, and statistical modeling with applications in marketing measurement.
- Expertise in Python, R, SQL, and cloud platforms (AWS, GCP, or Azure) for scalable modeling and data processing.
- Experience with experimental design and incrementality testing in digital and traditional media channels.
- Ability to communicate complex data science concepts to both technical and non-technical stakeholders, influencing business decisions
- Bachelor's Degree Quantitative Field (math, statistics, economics, computer science, physics, engineering, etc.)
- Master's/Advanced Degree Quantitative Field (math, statistics, economics, computer science, physics, engineering)
Responsibilities
- Lead the development and refinement of attribution models (MTA, MMM) to quantify the impact of media investments across channels (digital, social, TV, search, etc.).
- Advance causal inference techniques to improve media measurement, including uplift modeling, propensity scoring, and Bayesian methods.
- Develop forecasting models to predict marketing performance, budget allocation impacts, and long-term customer acquisition trends.
- Enhance ad testing methodologies, including A/B testing, synthetic control experiments, and incrementally testing, to measure media efficiency accurately.
- Collaborate with marketing, finance, and analytics teams to translate model insights into business strategies that drive ROI improvements.
- Optimize media spend through AI-driven decisioning, using reinforcement learning, Bayesian optimization, and econometric modeling.
- Stay at the forefront of AI & ML innovations in marketing measurement, driving technical advancements and thought leadership within the team.
Other
- At least 18 years of age
- Legally authorized to work in the United States
- Bachelor's Degree Quantitative Field (math, statistics, economics, computer science, physics, engineering, etc.)
- Ability to communicate complex data science concepts to both technical and non-technical stakeholders, influencing business decisions
- Must be located in Bellevue, WA, with a hybrid schedule requiring at least 3 days a week in office
