Job Description

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees!

T-Mobile’s Strategy and Corporate Development (S&CD) team is looking for a Principal Data Scientist who can build data-driven strategic insights.


Our team:


T-Mobile’s S&CD team is an internal consulting team that works with executive leaders from across the company. Leveraging deep problem-solving and advanced data skills, the team delivers insight and helps leaders make critical strategic and operational decision.


This role owns projects that tackle complex and ambiguous problems to drive transformational change (e.g. Customer-Driven Coverage).


As a Principal Data Scientist, you will tackle complex and ambiguous problems to drive transformational change (e.g. Customer-Driven Coverage). You will be responsible for combining the strategic and the technical. Beyond building advanced analytical, machine learning, and AI models, you will structure the problem-solving for projects, work with teams across T-Mobile, and identify the ‘so what’ for senior leaders making decisions.

Job Responsibilities :

• Extract, prepare, and model large, complex data sets using a combination of skills, including machine learning theory, mathematics, statistics, and programming.

• Identify critical and emerging technologies that will support and extend our consumer data, data integration, and quantitative analytic capabilities.

• Lead the implementation, assessment and standardization of advanced analytics and modeling toolkits for our data science team.

• Partner with data engineering teams to shape data management strategies, architecture, governance, pipelines, and infrastructure enabling effective modeling environments for data science teams

• Provide senior level guidance to the data science and measurement science teams on approach and methodologies.

• Communicate important information and insights to business leaders using verbal, written, and data visualization skills.

• Also responsible for other Duties/Projects as assigned by business management as needed.

Education :

• Bachelor's Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Required)

• Master's/Advanced Degree Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Preferred)

Work Experience :

• 7-10 years of industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)

• 7-10 years of Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data. (Required)

• 7-10 years of Experience with data scripting languages (e.g., SQL, Python, R) and Extended experience working with relational database using SQL (Required)

• 4-7 years of Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations (Required)

• 4-7 years of Experience with statistical methods and advanced modeling techniques. For example- SVM, Random Forest, graph models, Bayesian inference, NLP, Computer Vision, neural networks. (Required)

• 4-7 years of Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)

• 4-7 years of Experience in data visualization (Required)

• 2-4 years Management consulting, investment banking, or corporate strategy (Required)

• Experience in the telecom industry preferred.

Knowledge, Skills and Abilities :

• Mathematics: Calculus, linear algebra, statistics, and probability (Required)

• Programming: Mastery of Python and SQL (Required)

• Machine Learning: Apply machine learning techniques including supervised and unsupervised learning; collaborative filtering; and artificial neural networks (Required)

• Deep Learning: Research, design, implement, evaluate, and optimize novel algorithms/models in Deep Learning space (Required)

• Communication: Exemplary communication skills, ability to work with cross functional teams

• At least 18 years of age
• Legally authorized to work in the United States

Travel :
Travel Required (Yes/No):No



DOT Regulated :
DOT Regulated Position (Yes/No):No
Safety Sensitive Position (Yes/No):No

Base Pay Range: $127,400 - $229,800

Corporate 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, click here.

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

Never stop growing!
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.


Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.

Job Tags

Holiday work, Full time, Temporary work, Work experience placement, Local area, Flexible hours,

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