Job description

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 This role leads technical innovation within the data science function to address complex business challenges using advanced analytics and machine learning. It involves collaborating with diverse technical and non-technical stakeholders to develop advanced analytics and machine learning modeling solutions. The role requires mastery of existing machine learning techniques and development of artificial intelligence that supports key business operations. Success is measured by the effective implementation of advanced analytics, the adoption of emerging technologies, and the delivery of actionable insights. The work impacts the organization by enabling data-driven decision-making and advancing the technical capabilities of data science teams. Job Responsibilities : Extract, prepare, and model large, complex data sets to develop advanced analytics and machine learning solutions Identify and evaluate emerging technologies to enhance data integration and quantitative analytics capabilities Lead the implementation and standardization of advanced analytics and modeling toolkits for data science teams Collaborate with data engineering to shape data management strategies, architecture, governance, and infrastructure Provide senior-level guidance on data science methodologies and approaches to technical teams Communicate insights and technical information to business leaders through verbal, written, and visual means Also responsible for other duties/projects as assigned by business management as needed Education and Work Experience : Bachelor s Degree plus 7 years of related work experience OR Advanced degree with 5 years of related experience (Required) Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Required) 7-10 years Industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required) 4-7 years Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations (Required) 7-10 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required) 4-7 years Experience with statistical methods and advanced modeling techniques. For example- SVM, Random Forest, graph models, Bayesian inference, NLP, Computer Vision, neural networks (Required) 4-7 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required) 7-10 years Experience with data scripting languages (e.g., SQL, Python, R) (Required) 4-7 years Experience in data visualization (Required) 7-10 years Extended experience working with relational database using SQL (Required) 4-7 years Experience in telecom industry (Preferred) Knowledge, Skills and Abilities : Advanced Analytics (Required) Critical Thinking (Required) Data Science (Required) Data Visualization (Required) Deep Learning (Required) Generative AI (Required) Large Language Model (LLM) Fine-Tuning (Required) Machine Learning (ML) (Required) Statistical Analysis (Required) 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 Total Target Cash Earnings Opportunity: $152,880 - $275,760 National Base Pay Range: $127,400 - $229,800 The Total Target Cash Earnings Opportunity represents the expected total cash compensation for this role at target performance, combining base salary and annual incentive opportunity. Actual earnings may be higher or lower depending on individual performance and overall company results. The base pay range reflects the compensation component of this opportunity. The 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. To find the pay range for this role based on hiring location, paylookup.t-mobile.com 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. Corporate employees are eligible for a year-end bonus based on individual and/or company 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. The incentive component included in the Total Target Cash Earnings Opportunity reflects target performance. Actual earnings included in the Total Target Cash Earnings Opportunity reflect target performance; actual payouts may vary. 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, genetic information, 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.

Requirements

Must-haves

Job Overview
Extract, prepare, and model large, complex data sets to develop advanced analytics and machine learning solutions
Identify and evaluate emerging technologies to enhance data integration and quantitative analytics capabilities
Lead the implementation and standardization of advanced analytics and modeling toolkits for data science teams
Collaborate with data engineering to shape data management strategies, architecture, governance, and infrastructure
Provide senior-level guidance on data science methodologies and approaches to technical teams
Communicate insights and technical information to business leaders through verbal, written, and visual means
Also responsible for other duties/projects as assigned by business management as needed
Bachelor s Degree plus 7 years of related work experience OR Advanced degree with 5 years of related experience (Required)
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Required)
4-7 years Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations (Required)
7-10 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
4-7 years Experience with statistical methods and advanced modeling techniques. For example- SVM, Random Forest, graph models, Bayesian inference, NLP, Computer Vision, neural networks (Required)
4-7 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
7-10 years Experience with data scripting languages (e.g., SQL, Python, R) (Required)
4-7 years Experience in data visualization (Required)
7-10 years Extended experience working with relational database using SQL (Required)
Advanced Analytics (Required)
Critical Thinking (Required)
Data Science (Required)
Data Visualization (Required)
Deep Learning (Required)
Generative AI (Required)

Nice-to-haves

4-7 years Experience in telecom industry (Preferred)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlsqlpythonaillm

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off