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.

• 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.

• Bachelor's degree plus 5 years of related work experience OR advanced degree with 3 years of related experience; acceptable areas of study include quantitative disciplines (math, statistics, economics, computer science, physics, engineering, etc.).
• 4–7 years of experience in AI/ML model development, MLOps, and cloud‑based ML (Databricks, Azure ML, AWS Sage Maker, or similar) and libraries (PyTorch, Tensor Flow, Nixtla, XGBoost, LightGBM).
• 4–7 years of experience with data scripting languages (e.g., SQL, Python, R).
• 2–4 years of experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc.
• 4–7 years of experience translating business questions into AI‑driven solutions using supervised, unsupervised, and deep learning models.
• 4–7 years of experience in data visualization.
• 4–7 years of experience in MLOps, CI/CD pipelines, and automated model deployment.
• 2–4 years of 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 Required (Yes/No):
No

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

$106,000 – $191,100
Corporate Bonus Target: 15%

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…