What are the responsibilities and job description for the Sr. Data Scientist, Machine Learning position at T-Mobile?
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!
This role is an individual contributor that will work on a hybrid schedule of at least 3 days a week in either the Frisco, TX or Overland Park, KS office.
Job Overview
Senior Data Scientist, you are responsible for leading the application of AI and machine learning techniques to solve complex business problems within the Databricks and Azure ecosystems. You will collaborate with a multi-disciplinary team of technical and non-technical stakeholders, leveraging big data architectures, cloud computing, and advanced analytics. You must demonstrate expertise across the entire machine learning (ML) lifecycle, including problem framing, data collection, exploratory data analysis, model development, deployment, storytelling, and performance measurement. This role requires a strong foundation in Azure-based AI/ML services, Databricks workflows, and scalable machine learning pipelines, ensuring the development of robust and production-ready solutions.
Job Responsibilities:
Travel Required (Yes/No):No
DOT Regulated:
DOT Regulated Position (Yes/No):No
Safety Sensitive Position (Yes/No):No
Base Pay Range: $106,000 - $191,100
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, copy and paste this link into your browser: https://paylookup.t-mobile.com/paylookup?reqID=REQ303729
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 ApplicantAccommodation@t-mobile.com 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.
This role is an individual contributor that will work on a hybrid schedule of at least 3 days a week in either the Frisco, TX or Overland Park, KS office.
Job Overview
Senior Data Scientist, you are responsible for leading the application of AI and machine learning techniques to solve complex business problems within the Databricks and Azure ecosystems. You will collaborate with a multi-disciplinary team of technical and non-technical stakeholders, leveraging big data architectures, cloud computing, and advanced analytics. You must demonstrate expertise across the entire machine learning (ML) lifecycle, including problem framing, data collection, exploratory data analysis, model development, deployment, storytelling, and performance measurement. This role requires a strong foundation in Azure-based AI/ML services, Databricks workflows, and scalable machine learning pipelines, ensuring the development of robust and production-ready solutions.
Job Responsibilities:
- Extract, prepare, and model large, complex data sets using Databricks, Azure ML, and scalable AI/ML techniques. Apply cutting-edge deep learning, NLP, and reinforcement learning where applicable.
- Deliver on-time AI-driven insights and recommendations to enable intelligent decision-making across the business. Utilize Azure Synapse, Power BI, and Databricks dashboards for data storytelling.
- Work closely with data engineering teams to design and improve machine learning pipelines using Azure Data Factory, Databricks Delta Lake, and Spark.
- Effectively communicate AI-driven insights to business leaders, leveraging advanced visualization techniques and automated reporting tools.
- Also responsible for other Duties/Projects as assigned by business management as needed.
- Bachelor's Degree Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)
- Master's/Advanced Degree Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Preferred)
- 4-7 years experience in AI/ML model development, MLOps, and cloud-based ML (Databricks, Azure ML, AWS Sagemaker, or similar) and libraries (PyTorch, TensorFlow, Nixtla, XGBoost, LightGBM) (Required)
- 4-7 years experience with data scripting languages (e.g., SQL, Python, R) (Required)
- 2-4 years experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
- 4-7 years experience translating business questions into AI-driven solutions using supervised, unsupervised, and deep learning models (Required)
- 4-7 years experience in data visualization (Required)
- 4-7 years experience in MLOps, CI/CD pipelines, and automated model deployment (Required)
- 2-4 years Experience in the telecom industry (Preferred)
- Mathematics- Calculus, linear algebra, statistics, and probability (Required)
- Programming- Expertise in Python and SQL (Required)
- MLOps & Automation- Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning. Experience with CI/CD, MLflow, and model monitoring in production (Required)
- Communication Strong communication skills, ability to work with cross functional teams.
- At least 18 years of age
- Legally authorized to work in the United States
Travel Required (Yes/No):No
DOT Regulated:
DOT Regulated Position (Yes/No):No
Safety Sensitive Position (Yes/No):No
Base Pay Range: $106,000 - $191,100
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, copy and paste this link into your browser: https://paylookup.t-mobile.com/paylookup?reqID=REQ303729
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 ApplicantAccommodation@t-mobile.com 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.
Salary : $106,000 - $191,100