Senior Data Science Software Engineer

T-Mobile•Philadelphia, PA

1d•$116,500 - $210,100

About The Position

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 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.

Requirements

Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.)
4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools.
4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift)
4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS)
4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices.
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.
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Experience in AdTech and GIS or geospatial data processing is a plus.

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.