Principal Data Scientist

T-Mobile•Bellevue, WA

3d•$127,400 - $229,800

About The Position

This role leads technical innovation within T-Mobile’s data science function to address complex business challenges using advanced analytics and machine learning. It collaborates with technical and non-technical stakeholders to develop advanced analytics and machine learning solutions, applies established machine learning techniques, and develops artificial intelligence capabilities supporting key business operations. Success is measured by effective implementation of advanced analytics, adoption of emerging technologies, and delivery of actionable insights. The work enables data-driven decision-making and advances the technical capabilities of data science teams. The position requires a bachelor’s degree and seven years of related experience, or an advanced degree and five years of related experience. Acceptable fields include quantitative disciplines such as mathematics, statistics, economics, computer science, physics, and engineering. The posting describes substantial experience in predictive modeling, data science, model deployment or deep learning, data scripting, SQL, statistical modeling, big data technologies, data visualization, and communication of technical concepts. Telecom industry experience is preferred. Travel is not required. The role is not DOT-regulated or safety-sensitive. The national base pay range is $127,400–$229,800, and the total target cash earnings opportunity is $152,880–$275,760. Actual pay varies with factors such as work location, qualifications, and experience. Eligible employees may receive an annual bonus or other incentive, depending on role and performance.

Requirements

Bachelor’s degree plus 7 years of related work experience, or an advanced degree with 5 years of related experience.
Degree in a quantitative discipline such as mathematics, statistics, economics, computer science, physics, or engineering.
7–10 years of 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 of experience communicating technical concepts to business, technical, and lay audiences and giving data-driven presentations.
7–10 years of experience translating business questions and using statistical techniques to find answers using available data.
4–7 years of experience with statistical methods and advanced modeling techniques, such as SVM, Random Forest, graph models, Bayesian inference, NLP, computer vision, or 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, Python, or R.
4–7 years of experience in data visualization.
7–10 years of extended experience working with relational databases using SQL.
Knowledge of advanced analytics, critical thinking, data science, data visualization, deep learning, generative AI, LLM fine-tuning, machine learning, and statistical analysis.
At least 18 years of age.
Legally authorized to work in the United States.

Nice To Haves

4–7 years of experience in the telecom industry.

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 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 verbally, in writing, and visually.
Perform other duties or projects assigned by business management as needed.