Senior Data Science Engineer

Posted 9 Days Ago
2 Locations
In-Office
117K-210K Annually
Senior level
Other • Utilities
The Role
The Senior Data Science Engineer will lead the development of machine learning projects, build scalable data pipelines, and collaborate with teams to implement solutions while ensuring quality and business impact.
Summary Generated by Built In

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. That’s how we’re UNSTOPPABLE for our employees!

Job Overview
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.

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.

  • At least 18 years of age
  • Legally authorized to work in the United States

Travel:
Travel Required (Yes/No): No
DOT Regulated:
DOT Regulated Position (Yes/No): No
Safety Sensitive Position (Yes/No): 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 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. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, https://paylookup.t-mobile.com/paylookup?reqID=REQ356839¶dox=1

At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. 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 - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - 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. We don't stop there - 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, check out www.t-mobilebenefits.com.

Never stop growing!
As part of the T-Mobile team, you know the Un-carrier doesn’t have a corporate ladder–it’s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it’s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you’re living our values while investing in your career growth–and we applaud it. You’re unstoppable!
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.
Talent comes in all forms at the Un-carrier. 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 [email protected] or calling 1-844-873-9500. Please note, 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.

Skills Required

  • Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience
  • 4-7 years experience building and deploying machine learning and deep learning solutions at scale
  • 4-7 years Experience working within big data architecture and services
  • 4-7 years Experience with large-scale distributed data systems and cloud platforms
  • 4-7 years Experience solving complex data or algorithmic challenges in production environments

T-Mobile Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about T-Mobile and has not been reviewed or approved by T-Mobile.

  • Healthcare Strength Health coverage includes multiple medical plan types alongside dental and vision, with virtual care and mental‑health options included. LiveMagenta support and dedicated health‑care advocates provide accessible guidance and care navigation.
  • Equity Value & Accessibility Equity participation includes annual stock grants for eligible roles and a 15%‑discount ESPP with a lookback, extending value beyond base pay. Feedback suggests these equity programs are a meaningful component of total rewards.
  • Parental & Family Support Family‑building and caregiving support spans paid parental and family leave, Progyny fertility, adoption/surrogacy reimbursements, doula support, and backup care. Income‑based childcare subsidies further ease costs for eligible employees.

T-Mobile Insights

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The Company
HQ: Bellevue, WA
89,016 Employees

What We Do

T-Mobile U.S. Inc. (NASDAQ: TMUS) is America’s supercharged Un-carrier, delivering an advanced 4G LTE and transformative nationwide 5G network that will offer reliable connectivity for all. T-Mobile’s customers benefit from its unmatched combination of value and quality, unwavering obsession with offering them the best possible service experience and undisputable drive for disruption that creates competition and innovation in wireless and beyond. Based in Bellevue, Wash., T-Mobile provides services through its subsidiaries and operates its flagship brands, T-Mobile, Metro by T-Mobile and Sprint.

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