Principal Data Scientist

T-Mobile

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Hybrid

Quick summary

Work type: Hybrid
Location: Overland Park, KSSeattle, WA
Employment: Full-time
Posted: 6 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $186k

$121k $236k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $158,298–$214,500.

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 42 open roles on FindRole.

Listed pay typically runs $134,722–$228,650 across 18 roles with salary data.

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At a glance

TL;DR · Principal Data Scientist

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The Principal Data Scientist drives technical innovation across the data science function by applying advanced analytics, machine learning, and artificial intelligence to solve complex business challenges. This role involves extracting, preparing, and modeling large, complex data sets to develop modeling solutions that support critical operations. Key responsibilities include owning the implementation and standardization of modeling toolkits, collaborating with data engineering on architecture and governance, and providing senior-level guidance on methodologies. The position requires proficiency in SQL, Python, Hadoop, Hive, Spark, and Kafka. Candidates must demonstrate expertise in statistical methods such as SVM, Random Forest, Bayesian inference, NLP, and Computer Vision. Additionally, the role utilizes Generative AI, Large Language Models, and tools like Databricks, XGBoost, and PySpark to deliver actionable insights within a telecom context.

What does a Data Scientist earn in Washington?

Median $198000 from 42 postings across 15 companies.

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Skills

Python SQL Machine Learning Deep Learning Generative AI Large Language Model (LLM) PySpark Spark Hadoop Hive Kafka Data Bricks XGBoost LGBM NLP Computer Vision Statistical Analysis Data Visualization SVM Random Forest Bayesian Inference

What you'll do

Extract, prepare, and model large, complex data sets to develop advanced analytics and machine learning solutions.
Identify and evaluate new technologies to enhance data integration and quantitative analytics capabilities.
Own the 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 through verbal, written, and visual means.

What we're looking for

Must be at least 18 years of age and legally authorized to work in the United States.
Bachelor's degree with 7 years of related experience or an advanced degree with 5 years of related experience in a quantitative discipline.
7-10 years of industry experience in predictive modeling, data science, and analysis as an ML engineer or data scientist.
7-10 years of experience with data scripting languages like SQL and Python, and 7-10 years of experience with relational databases using SQL.
4-7 years of experience with statistical methods, advanced modeling techniques, and big data architecture including Hadoop, Hive, and Spark.
4-7 years of experience in data visualization and 4-7 years of experience communicating technical concepts to diverse audiences.
Proficiency in advanced analytics, machine learning, generative AI, large language models, and statistical analysis.
4-7 years of experience in the telecom industry (preferred).

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