below marketmost similar roles pay hereabove market
This role pays more than
58%
of similar roles. Most pay
$135,000–$213,756
— the blue band above.
At the midpoint, this role pays about
$169k
versus about
$174k
for comparable roles.
Based on 240 similar postings.
Employer
About T-Mobile
T-Mobile US is the second-largest wireless carrier in the United States, providing wireless voice, messaging, and data services under the T-Mobile and Metro by T-Mobile brands. Industry: Wireless Telecommunications
T-Mobile currently has
72 open roles
on FindRole.
Listed pay typically runs
$138,996–$228,650
across 32 roles with salary data.
Sr Data Scientists will join the team to develop forecasting models that predict marketing performance, budget allocation impacts, and long-term customer acquisition trends. The role involves diagnosing and resolving statistical model failures, monitoring outputs for accuracy and drift, and running scenario-based forecasts to support business planning. Key responsibilities include collaborating with marketing, finance, and analytics teams to translate model insights into strategies that improve ROI, while working with data engineers to automate model deployment in production environments. Candidates must utilize Python, R, and SQL across AWS, GCP, and Azure cloud platforms. Required expertise includes marketing and media analytics, causal inference methodologies like Bayesian structural time series, and building dashboards in Tableau or PowerBI. The role focuses on solving complex marketing measurement problems through advanced machine learning and statistical modeling.
Use Python and SQL to diagnose, resolve, and monitor statistical model failures and data drift.
Develop forecasting models to predict marketing performance, budget impacts, and customer acquisition trends.
Run and analyze scenario-based forecasts using Tableau and Power BI to support business planning.
Work with data engineers to scale and automate model deployment into production environments.
Design and execute statistical validation, hypothesis testing, and A/B testing frameworks.
Build business reports and dashboards to identify optimization opportunities and drive ROI.
Apply causal inference methodologies and media mix optimization techniques to marketing analytics.
What we're looking for
Master’s degree in Business Analytics, Economics, Engineering, Physics, Mathematics, Statistics, or related field and 3 years of relevant work experience.
Bachelor’s degree in Business Analytics, Economics, Engineering, Physics, Mathematics, Statistics, or related field and 5 years of relevant work experience.
Experience using Python and R to build, train, validate, and maintain statistical and machine-learning models in production environments.
Experience using SQL and cloud platforms including AWS, GCP, and Azure for scalable data ingestion and analytical workflows.
Experience in marketing and media analytics, including media attribution, causal inference, and media mix optimization.
Experience building business reports and dashboards using Tableau or PowerBI.
Experience designing and executing statistical validation, hypothesis testing, and A/B testing frameworks.
Must be legally authorized to work in the United States.
Generative AI
Machine Learning
Natural Language Processing
Large Language Models
Python
SQL
LangChain
DSPy
MLOps
Data Science
Multi-objective Optimization
Real-World Data
Data Visualization
Business Intelligence
Database Management