Principal Data Scientists

T-Mobile

Hybrid

Quick summary

Work type
Hybrid
Location
Bellevue, WA
Salary
$196,914–$224,000 / yr
Posted
3 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $157k
This role $210k
$96k most similar roles pay here $238k

This role pays more than 84% of similar roles. Most pay $126,800–$188,050 — the shaded band above. At the midpoint, this role pays about $210k versus about $157k for comparable roles.

Based on 240 similar postings.

Employer

About T-Mobile

T-Mobile US is the second-largest wireless carrier in the United States, providing wireless voice, messaging, and data services under the T-Mobile and Metro by T-Mobile brands. Industry: Wireless Telecommunications

T-Mobile currently has 15 open roles on FindRole.

Listed pay typically runs $116,500–$205,000 across 15 roles with salary data.

Most-posted roles

View all roles at T-Mobile

At a glance

TL;DR · Principal Data Scientists

As a Principal Data Scientist at T-Mobile in Bellevue, WA, you will lead the development of advanced statistical and machine learning models to forecast business outcomes like service activations and digital traffic. Your day-to-day involves designing scalable modeling pipelines in Python, ensuring reproducibility and operational readiness, while also mentoring junior data scientists and collaborating with cross-functional teams to integrate forecasting outputs into decision-making processes. You must stay current with advances in statistical methods and machine learning techniques, such as ensemble models and deep learning, and communicate complex findings through clear documentation and presentations. The role requires expertise in SQL, Python, Azure Databricks, AWS, and a strong background in economics, mathematics, or statistics, typically at the master’s level with 5 years of relevant experience.

What you'll do

  • Design advanced statistical and machine learning models to forecast business outcomes like service activations and traffic.
  • Develop media attribution models including Marketing Mix Modeling and Multi-Touch Attribution for evaluating marketing effectiveness.
  • Guide the deployment of scalable modeling pipelines in Python to ensure reproducibility and operational readiness.
  • Mentor junior data scientists, providing methodological direction, feedback, and quality control.
  • Innovate and refine forecasting methods using classic and innovative statistical techniques like ensemble models and deep learning.
  • Communicate complex findings through presentations, documentation, and visualizations to support decision-making for stakeholders.

What we're looking for

  • Master’s degree in a quantitative field plus 5 years of relevant data science experience or equivalent combination of education and experience.
  • Develop advanced statistical and machine learning models for forecasting business outcomes using Python and SQL.
  • Design and refine media attribution models like Marketing Mix Modeling and Multi-Touch Attribution to evaluate marketing effectiveness.
  • Guide the development of scalable modeling pipelines in Python, ensuring reproducibility and operational readiness.
  • Mentor junior data scientists, providing methodological direction, feedback, and quality control.

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