Device & Supply Chain is an enterprise function accountable for the end-to-end life-cycle of T-Mobile’s consumer-facing hardware portfolio (phones, chipsets, accessories, IoT), device services portfolio (insurance, warranty, trade-ins, and financing), and supply chain operations (distribution centers, logistics, inventory, etc.).
This team also oversees the services we offer for device financing, mobile banking, and managing the millions of phones that get returned each year from our device services like remorse, trade-ins, lease returns, and JUMP!.
Supply Chain Data Analytics and Operations Research team is responsible for bringing ideas and developing technologies for step function changes in the Devices and Supply Chain organization. We develop models and algorithms using operations research and artificial intelligence to solve business problems and to improve T-Mobile revenue, cost, and customer satisfaction. We provide data driven insights to business teams and leadership in their operational, tactical, and strategic decision making. We develop tools and technologies to automate and to minimize human interventions in recurring decisions.
Leading thought processes and technical works for high impact and game changing projects in devices and supply chain organization
Identifying opportunities where T-Mobile forward and reverse logistics lag and develop cutting edge technologies to close them using data mining, machine learning, and artificial intelligence
Bringing ideas which will drive significant cost cutting/revenue improvements in T-Mobile’s sales and operations
Establishing data pipelines and ML frameworks, and driving innovations in artificial intelligence in devices supply chain organization
Developing machine learning (ML) models, such as to improve supply/demand forecasts, predict customer behaviors and responses, improve revenue, and reduce supply chain costs
Working with IT teams to implement production data and ML models in Azure cloud platform
Routinely partnering with T-Mobile marketing, commercial, retail, and customer care teams to drive alignment and success in T-Mobile device and supply chain opportunities
Mentoring and leading junior team members in technical areas
M.S. degree in Computer Science, Statistics, Operations Research, Mathematics, or in a related engineering/science field
Outstanding ability to research and model abstract and not-well defined problems
5+ years of experience in data mining and insights generation
5+ years of demonstrated experience in development and implementation of machine learning models, preferably in cloud environments, such as decision trees (Random Forest, XG boosting), neural networks, clustering, forecasting, time series
Superb database querying and data mining skills in SQL, Python, and R
Expert knowledge and experience in programming with Python, R, and Java
Excellent presentation and communication skills. Ability to effectively communicate technical works to non-technical audiences.
Flexible, self-starter, and comfortable working in a rapidly changing environment
Desire for a high level of responsibility and work in a team oriented environment
At least 18 years of age
Legally authorized to work in the United States
High School Diploma or GED
As America’s Un-carrier, T-Mobile USA, Inc. (NASDAQ: “TMUS”) is redefining the way consumers and businesses buy wireless services through leading product and service innovation. The company’s advanced nationwide 4G and 4G LTE network delivers outstanding wireless experiences for customers who are unwilling to compromise on quality and value. Based in Bellevue, Washington, T-Mobile USA. Inc. provides services through its subsidiaries and operates its flagship brands, T-Mobile and Metro by T-Mobile. For more information, please visit http://www.t-mobile.com
We Take Equal Opportunity Seriously - By Choice. 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, 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 or harassment based upon any of these factors is wholly inconsistent with our Company values and will not be tolerated. Furthermore, such discrimination or harassment may violate federal, state, or local law.