Principal Data Scientist

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Principal Data Scientist – Media Attribution
The Principal Data Scientist – Media Attribution will lead the development of cutting-edge machine learning and AI-driven models to optimize marketing spend, measure media effectiveness, and drive business outcomes. This role sits within the Media Analytics team, which provides actionable insights to enhance paid media efficiency through data-driven analytics, attribution modeling, ad testing, and forecasting.
As a senior technical leader, the Principal Data Scientist will collaborate with business stakeholders, data engineers, and analysts to develop advanced measurement frameworks, improve attribution models, and create AI-driven optimizations for media investments. The ideal candidate will have deep expertise in causal inference, multi-touch attribution (MTA), marketing mix modeling (MMM), and experimental design, ensuring that marketing strategies are backed by robust, data-driven insights.

Key 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 incrementality testing, to measure media effectiveness 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, leveraging 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.
• Work closely with data engineers to scale and automate model deployment, integrating ML solutions into production environments.

Required Qualifications:

• 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.
• Ph.D. or Master’s degree in a quantitative field (e.g., Statistics, Economics, Computer Science, Applied Mathematics).

This role is ideal for a hands-on, forward-thinking data science leader who is passionate about driving business impact through AI and machine learning in marketing measurement. If you thrive at the intersection of advanced analytics and strategic decision-making, we’d love to hear from you!

Base Pay Range: $127,400 - $229,800Corporate Bonus Target: 20%

The pay range above is the general base pay range for a successful candidate in the role. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.

At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee’s eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, https://paylookup.t-mobile.com/paylookup?reqID=REQ306050¶dox=1

At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile’s amazing benefits, check out www.t-mobilebenefits.com.

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As part of the T-Mobile team, you know the Un-carrier doesn’t have a corporate ladder–it’s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it’s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you’re living our values while investing in your career growth–and we applaud it. You’re unstoppable!

T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated.

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