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.

• 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.

• 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 Dev Ops 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., Big Query, 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)

• 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 age
• Legally authorized to work in the United States

Travel Required:

No

DOT Regulated Position:
No

Safety Sensitive Position:
No

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…