Senior Applied Scientist

Overview 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. At 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 Applied Scientist 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. Employment Eligibility At least 18 years of age Legally authorized to work in the United States Travel and Safety Travel Required: No DOT Regulated Position: No Safety Sensitive Position: No Pay and Benefits Base Pay Range: $116,500 - $210,100. Corporate Bonus Target: 15%. 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. 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, 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. 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, visit Equal Opportunity Employer 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. 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 View email address on click.appcast.io or calling View phone number on click.appcast.io. The 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. #J-18808-Ljbffr