Sr. Data Scientist AI COE

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As a 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.

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.
• Provide senior-level guidance and mentorship to the data science team ensuring best practices in MLOps model governance and cloud-based deployment.
• 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.

Qualifications:

• Bachelors degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience; Acceptable areas of study include Quantitative Discipline (math statistics economics computer science physics engineering etc.)
• 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)
• 4-7 years Experience with data scripting languages (e.g. SQL Python R)
• 2-4 years Experience with big data architecture and pipeline Hadoop Hive Spark Kafka etc.
• 4-7 years Experience translating business questions into AI-driven solutions using supervised unsupervised and deep learning models
• 4-7 years Experience in data visualization
• 4-7 years Experience in MLOps CI/CD pipelines and automated model deployment
• 2-4 years Experience in the telecom industry preferred
• Calculus linear algebra statistics and probability knowledge
• Expertise in Python and SQL required
• 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
• 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:
Travel Required (Yes/No): No

DOT Regulated:
DOT Regulated Position (Yes/No): No
Safety Sensitive Position (Yes/No): No

Base Pay Range: $106000 - $191100

Corporate Bonus Target: 15%

The pay range above is the general base pay range for a successful candidate in the role. The successful candidates 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 employees 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 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 dont 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-Mobiles amazing benefits check out.

Never stop growing!
As part of the T-Mobile team you know the Un-carrier doesnt have a corporate ladderits more like a jungle gym of possibilities! We love helping our employees grow in their careers because its that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity youre living our values while investing in your career growthand we applaud it. Youre 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.

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