At T-Mobile, the business problem is to drive insights, shape strategy, and make a measurable impact through deep data science to accelerate growth, optimize performance, and transform the way T-Mobile delivers fiber across the country.
Requirements
- Strong proficiency in Python and SQL; experience with R is a plus.
- Hands-on experience building data pipelines, crafting visualizations, and communicating insights.
- Solid understanding of supervised and unsupervised machine learning techniques.
- Ability to break down complex problems, think critically, and solve analytically.
- Experience working with stakeholders and adapting to shifting priorities in fast-paced environments.
- 2–4 years of experience in data science, predictive modeling, or ML engineering.
- Telecom experience (2–4 years) strongly preferred.
Responsibilities
- Analyze massive, complex datasets to uncover insights and power smarter decision-making.
- Apply machine learning, statistics, and modeling to tackle critical business questions like customer acquisition, penetration optimization, and product performance.
- Build and iterate on advanced predictive models—especially focused on penetration permutations and regional financial performance.
- Create and test challenger models to constantly improve accuracy and effectiveness.
- Develop near real-time scorecards to track cohort performance and signal when interventions are needed.
- Collaborate with stakeholders to visualize and present findings through compelling dashboards and storytelling.
- Translate complex technical insights into clear, actionable strategies for business leaders.
Other
- Bachelor’s Degree in a quantitative field such as Math, Statistics, Computer Science, Physics, or Engineering is required.
- Master’s or other advanced degree preferred.
- At least 18 years of age
- Legally authorized to work in the United States
- Three days in the office in a hybrid work environment
