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!Job OverviewAt T-Mobile Advertising Solutions, we're building privacy-first advertising products powered by advanced machine learning, large-scale data processing, and cloud technologies. Our proprietary algorithms enable rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy. We are seeking a creative, and curious Senior Data Science Software Engineer to join our team. In this role, you'll work at the intersection of machine learning, software engineering, and big data, building AI and ML systems that directly impact our customers and business. You'll collaborate with engineers, data scientists, product managers, and other stakeholders to solve complex problems and deliver innovative solutions at scale. We embrace Lean Development principles, iterative experimentation, continuous learning, and a strong build-measure-learn feedback culture. The work you do will directly shape the future of our products and technologies.Job Responsibilities:Lead the end-to-end development of machine learning and data products aligned to business objectives, from problem framing through deployment and monitoring. Build scalable data, training, and inference pipelines using distributed processing and cloud technologies. Apply statistical methods, experimentation, and validation frameworks to ensure solution quality and business impact. Write production-quality code and contribute to engineering best practices, including testing, CI/CD, and observability. Collaborate across engineering, product, and business teams while leading other engineers and data scientists. Education and Work Experience:Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools. (Required)4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift) (Required)4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS) (Required)4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices.(Required)Knowledge, Skills and Abilities:Strong background in AI/ML, data structures, statistical modeling, optimization algorithms, big data, and design thinking.Advanced knowledge of cloud-based services (GCP, AWS) and Python, PySpark and related Python libraries (e.g. pandas, scikit-learn, scipy, numpy) for advanced data science tasks. Hands-on implementation and architectural familiarity with streaming data, relational and non-relational databases, and distributed processing technologies. Experience operating production machine learning and data systems in cloud and containerized environments. Experience in AdTech and GIS or geospatial data processing is a plus.At least 18 years of ageLegally authorized to work in the United StatesTravel:Travel Required (Yes/No): NoDOT Regulated:DOT Regulated Position (Yes/No): NoSafety Sensitive Position (Yes/No): NoTotal Target Cash Earnings Opportunity: $133,975 - $241,615National Base Pay Range: $116,500 - $210,100The 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=REQ356839¶dox=1At 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.