Senior Data Science Engineer

T-Mobile

Quick summary

Work type
On-site
Location
Philadelphia, PA · New York, NY
Salary
$116,500–$210,100 / yr
Posted
3 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $172k
This role $163k
$104k most similar roles pay here $233k

This role pays more than 51% of similar roles. Most pay $135,000–$209,000 — the shaded band above. At the midpoint, this role pays about $163k versus about $172k for comparable roles.

Based on 240 similar postings.

Employer

About T-Mobile

T-Mobile US is the second-largest wireless carrier in the United States, providing wireless voice, messaging, and data services under the T-Mobile and Metro by T-Mobile brands. Industry: Wireless Telecommunications

T-Mobile currently has 15 open roles on FindRole.

Listed pay typically runs $116,500–$205,000 across 15 roles with salary data.

Most-posted roles

View all roles at T-Mobile

At a glance

TL;DR · Senior Data Science Engineer

As a Senior Data Science Software Engineer at T-Mobile Advertising Solutions, you will join a dynamic team dedicated to developing privacy-first advertising products using advanced machine learning and big data technologies. Your daily responsibilities include leading the end-to-end development of AI and ML systems from problem framing through deployment, building scalable data pipelines with distributed processing and cloud technologies, and applying statistical methods for solution validation. You will write production-quality code, contribute to engineering best practices, and collaborate across teams to deliver innovative solutions at scale. The role requires expertise in Python, PySpark, and related libraries, as well as experience with large-scale distributed systems and cloud platforms like AWS or GCP. Ideal candidates have a strong background in AI/ML, data structures, statistical modeling, and hands-on experience with streaming data and containerized environments.

What you'll do

  • Lead end-to-end development of ML and data products from problem framing to deployment.
  • Build scalable data pipelines using distributed processing and cloud technologies.
  • Apply statistical methods and validation frameworks to ensure solution quality.
  • Write production-quality code and contribute to engineering best practices.
  • Collaborate with cross-functional teams while leading other engineers and data scientists.

What we're looking for

  • 4-7 years of experience building and deploying machine learning solutions at scale.
  • Proficient in MLOps and DevOps practices with hands-on cloud platform experience.
  • Strong background in big data architecture and large-scale data warehousing technologies.
  • Expertise in distributed data systems, including SQL, Python, Scala, and AWS/GCP.
  • Experience solving complex production challenges using modern engineering practices.
  • Hands-on implementation of streaming data, databases, and distributed processing technologies.
  • Knowledge of cloud-based services for operating production machine learning systems.

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