Sr Data Scientists

T-Mobile•Bellevue, WA

6d•Hybrid

About The Position

T-Mobile is hiring Sr Data Scientists to develop forecasting models that predict marketing performance, the impacts of budget allocation, and long-term customer acquisition trends. The role is based in Bellevue, Washington. Telecommuting is permitted, but the employee must work from the worksite at least 3–4 days per week. No additional national or international travel is anticipated. The position uses statistical and machine-learning models to support marketing measurement and business planning. The Sr Data Scientist diagnoses model failures, monitors accuracy and drift, investigates changes in performance, and analyzes scenario-based forecasts. The role also collaborates with marketing, finance, analytics, and data engineering teams to translate model insights into business strategies, improve ROI, and scale model deployment into production. The employee is expected to keep current with AI and machine-learning developments in marketing measurement and contribute technical advancements and thought leadership. The role requires either a relevant master’s degree or foreign equivalent and three years of relevant work experience, or a relevant bachelor’s degree or foreign equivalent and five years of relevant work experience. Work hours are 40 hours per week. The listed annual salary range is $166,036–$171,036; actual pay depends on factors including work location, qualifications, and experience.

Requirements

Master’s degree or foreign equivalent in Business Analytics, Economics, Engineering, Physics, Mathematics, Statistics, or a related field, plus three years of relevant work experience; alternatively, a bachelor’s degree or foreign equivalent in one of these fields plus five years of relevant work experience.
Experience using Python and R to build, train, validate, and maintain statistical and machine-learning models in production, including diagnosing model failures and performance degradation.
Experience with SQL and AWS, GCP, and Azure for scalable data ingestion, transformation, and analytical workflows.
Experience in marketing and media analytics, including media attribution using Google Marketing Platform and Adobe Analytics, and causal inference methods such as Bayesian structural time series, media holdout testing, and advanced media mix optimization.
Experience interpreting predictive analytical models developed with machine-learning and statistical frameworks, including regression and decision-tree techniques, using goodness-of-fit metrics, drift diagnostics, scenario testing, and sensitivity analysis.
Experience designing and executing statistical validation, hypothesis testing, and experimentation frameworks using Python- and R-based statistical libraries and controlled A/B testing frameworks to assess model performance, quantify uncertainty, and support business decisions.
Experience building business reports and dashboards using Tableau or Power BI to standardize reporting and identify optimization opportunities.
At least 18 years of age.
Legally authorized to work in the United States.

Responsibilities

Use Python to diagnose and resolve statistical model failures caused by data or code issues.
Use Python and SQL to monitor statistical model outputs, assess accuracy, and detect signs of drift.
Investigate changes in model accuracy and performance and flag concerns.
Run and analyze scenario-based forecasts to support business planning using Tableau and Power BI.
Collaborate with marketing, finance, and analytics teams to translate model insights into business strategies that improve ROI.
Work with data engineers to scale and automate model deployment and integrate machine-learning solutions into production environments.
Stay current with AI and machine-learning innovations in marketing measurement and drive technical advancements and thought leadership within the team.

Benefits

Competitive base salary and compensation package
Annual stock grant
Employee stock purchase plan
401(k)
Access to free, year-round money coaches
Annual bonus or periodic sales incentive or bonus, depending on role and eligibility
Medical, dental, and vision insurance
Flexible spending account
Paid time off and up to 12 paid holidays
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, accident, life, disability, and long-term care coverage
Mobile service and home internet discounts for eligible employees
Pet insurance for eligible employees
Commuter and transit programs for eligible employees