T-Ads Engineer, Data Science

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Job Description

The T-Ads Engineer, Data Science builds and deploys production-grade machine learning models and data pipelines within established architectural patterns. This role translates defined business problems into scalable technical solutions and executes across the full ML lifecycle under appropriate technical guidance. The engineer implements statistically sound models, contributes to pipeline design, and ensures reliable production deployment using engineering best practices. Success is measured by high-quality execution, technical depth, and consistent delivery of well-engineered ML components that drive business value.

Job Responsibilities: • Owns delivery of well-scoped ML systems or major components of larger systems, operating within established architectural standards and technical direction. • Translates moderately complex business problems into technical approaches, proposing solution options within defined architectural constraints. • Implements statistically rigorous solutions, applying appropriate testing, validation, and evaluation techniques aligned to defined business metrics. • Designs, trains, tunes, and deploys ML/deep learning models using established techniques with evaluation frameworks aligned to business metrics. • Implements scalable training and deployment pipelines using PySpark, Snowpark or similar technologies. Understands batch/streaming, distributed processing and cloud technologies as required for projects. • Writes production-ready code in common data science languages like Python (including AI/ML libraries), SQL, Scala; enforces engineering standards including CI/CD and automated testing. • Collaborates across engineering, product, and business stakeholders. • Contributes to technical design documentation and actively participates in peer design reviews. • Applies lean development principles by delivering solutions iteratively, validating impact through measurable outcomes, incorporating stakeholder feedback, and continuously refining models and systems using data-driven build–measure–learn cycles.

Work and Experience: • Bachelor's Degree plus 2 years of related work experience OR combination of education and experience deemed equivalent (Required) • Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required) • 2-4 years Industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML/deep learning models (Required) • 2-4 years Experience with common AI/ML programming languages (e.g., SQL, Python, Scala) (Required) • 2-4 years Experience designing and working within big data architectures using distributed processing and storage technologies (e.g., Spark, Snowflake, Hadoop, Hive, Kafka), along with hands-on experience leveraging cloud platforms (e.g., AWS, GCP, Azure) to build scalable, reliable, and production-grade data and machine learning systems (Required) • 2-4 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required) • 2-4 years Experience working with relational and non-relational databases using SQL (Required) • 2-4 years Experience in data visualization (Required)

Knowledges, Skills, and Abilities: • Ability to rigorously structure ambiguous problems, evaluate competing technical approaches using statistical and systems reasoning, anticipate failure modes, and make defensible decisions aligned to business impact. (Required) • Ability to design statistically defensible evaluations, detect subtle validity issues, and quantify uncertainty in business-facing decisions. (Required) • Machine Learning: Ability to design and implement ML solutions within established system architectures, select appropriate model classes and loss functions aligned to business objectives, implement robust cross-validation and hyperparameter optimization strategies, productionize models via reproducible pipelines and CI/CD practices, and continuously monitor for drift, robustness issues, and system-level constraints (scalability, reliability, observability, and cost). (Required) • Advanced proficiency in Python and PySpark, including extensive use of data science and ML libraries (e.g., pandas, NumPy, SciPy, scikit-learn) to build scalable data and modeling solutions. (Required) • Demonstrated ability to design and implement robust, efficient, and maintainable code using sound software engineering principles (modular design, testing, version control, CI/CD), including experience packaging and deploying applications using containerization technologies such as Docker, with working knowledge of Scala in distributed Spark environments when required. (Required) • Strong communication skills, ability to work with cross functional teams. (Required)

• 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

Total Target Cash Earnings Opportunity: $112,930 - $225,745

National Base Pay Range: $98,200 - $196,300

The Total Target Cash Earnings Opportunity represents the expected total cash compensation for this role at target performance, combining base salary and annual incentive opportunity. Actual earnings may be higher or lower depending on individual performance and overall company results.

The base pay range reflects the compensation component of this opportunity. The 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. To find the pay range for this role based on hiring location, https://paylookup.t-mobile.com/paylookup?reqID=REQ378424¶dox=1

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. Corporate employees are eligible for a year-end bonus based on individual and/or company 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. The incentive component included in the Total Target Cash Earnings Opportunity reflects target performance. Actual earnings included in the Total Target Cash Earnings Opportunity reflect target performance; actual payouts may vary.

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.

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, genetic information, 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.