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** This is not a remote position. T-Mobile is a hybrid work environment requiring work in the office three (3) days per week. The successful candidate will be located in either Seattle, Washington or Overland Park, Kansas areas.**Job Overview
This role drives technical innovation across the data science function, applying advanced analytics, machine learning, and artificial intelligence to solve complex business challenges. It partners with technical and non-technical stakeholders to develop modeling solutions that support critical operations. Success is measured by effective implementation, adoption of emerging technologies, and delivery of actionable insights that strengthen data-driven decision-making and advance team capabilities.
Job Responsibilities:
- Extract, prepare, and model large, complex data sets to develop advanced analytics and machine learning solutions
- Identify and evaluate new technologies to enhance data integration and quantitative analytics capabilities
- Own 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
Required Education:
- Bachelor's Degree plus 7 years of related work experience OR Advanced degree with 5 years of related experience . Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering)
Required Experience
- 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
- 4-7 years Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations
- 7-10 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
- 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
- 4-7 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc.
- 7-10 years Experience with data scripting languages (e.g., SQL, Python)
- 4-7 years Experience in data visualization
- 7-10 years Extended experience working with relational database using SQL
Preferred Experience
- 4-7 years Experience in telecom industry
Required Knowledge, Skills and Abilities:
- Advanced Analytics
- Critical Thinking
- Data Science
- Data Visualization
- Generative AI
- Large Language Model (LLM)
- Machine Learning (ML)
- Statistical Analysis
Preferred Knowledge, Skills and Abilities:
- Data Bricks
- Deep Learning
- XGBoost
- LGBM
- PySpark
- Reinforced Learning
#LI-Corporate
- 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 - $275,760National 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, https://paylookup.t-mobile.com/paylookup?reqID=REQ372571¶dox=1At 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.
Skills Required
- Bachelor's degree in mathematics, statistics, economics, computer science, physics, engineering, or another quantitative discipline, plus 7 years of related experience; or an advanced degree plus 5 years of related experience
- 7–10 years of industry experience in predictive modeling, data science, and analysis as an ML engineer or data scientist, including building and deploying machine learning models or developing deep learning models
- 4–7 years of experience communicating technical concepts to business, technical, and lay audiences and delivering data-driven presentations
- 7–10 years of experience translating business questions and applying statistical techniques to reach data-driven answers
- 4–7 years of experience with statistical methods and advanced modeling techniques, such as SVM, Random Forest, graph models, Bayesian inference, NLP, computer vision, and neural networks
- 4–7 years of experience with big data architecture and pipelines, including Hadoop, Hive, Spark, or Kafka
- 7–10 years of experience with data scripting languages such as SQL and Python
- 4–7 years of experience in data visualization
- 7–10 years of experience working with relational databases using SQL
- 4–7 years of experience in the telecommunications industry
- Legally authorized to work in the United States
- At least 18 years of age
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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