Senior Data Science Engineer

T-Mobile; Philadelphia (Philadelphia County); On-site; USD 116,500 - 210,100; Full time

Job summary

T-Mobile is seeking a Senior Data Science Software Engineer to develop AI and ML systems that significantly impact customers. You will lead the end-to-end development of machine learning products, collaborate with engineering and business teams, and apply statistical methods to ensure high-quality solutions.

Successful candidates will have a strong background in AI/ML and a Bachelor’s degree along with 5 years' experience in related fields. The position is based in Philadelphia, offering competitive pay and a bonus target.

Qualifications

• 5 years of related work experience in a quantitative discipline required.
• Experience with machine learning and deep learning solutions at scale.
• Familiarity with MLOps and DevOps practices.

Responsibilities

• Lead the end-to-end development of machine learning products.
• Build scalable data and inference pipelines using cloud technologies.
• Collaborate with engineers and business teams.

Skills

Strong background in AI/ML

Statistical modeling

Optimization algorithms

Big data

Design thinking

Education

Bachelor’s degree in a quantitative discipline

Tools

Python

PySpark

AWS

BigQuery

Snowflake

Redshift

Job description

Job Overview

At T-Mobile Advertising Solutions, we build privacy‑first advertising products powered by advanced machine learning, large‑scale data processing, and cloud technologies. Our proprietary algorithms deliver rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy. We are seeking a creative, curious Senior Data Science Software Engineer who will work at the intersection of machine learning, software engineering, and big data, building AI and ML systems that directly impact our customers and business.

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 disciplines (math, statistics, economics, computer science, physics, engineering, etc.) (required).
• 4–7 years of experience building and deploying machine learning and deep learning solutions at scale, familiarity with MLOps and DevOps practices and tools (required).
• 4–7 years of 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 of experience working with large‑scale distributed data systems and cloud platforms (e.g., SQL, Python, Scala, AWS) (required).
• 4–7 years of experience solving complex data, machine learning, or algorithmic challenges in a 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.

Additional Requirements

• 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%.

Equal Opportunity Employment

T‑Mobile USA, Inc. is an equal opportunity employer. All employment decisions are 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.

Accommodation

If you have a disability and need a reasonable accommodation at any point in the application or interview process, please email [e-mail] or call 1‑844‑873‑9500. 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.