Principal Data Scientist

Key Skills

Aartificial intelligence, Apache Hadoop, Apache Hive, Apache Kafka, AWS, Azure, Big Data Technology, Data Visualization, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, Python Programming, R Programming, Spark Core, SQL

Job Description

This job can be located anywhere within the United States.

T-Mobile is America’s supercharged Un-carrier, delivering an advanced 4G LTE and transformative nationwide 5G network that will offer reliable connectivity for all! The Principal Data Scientist will be part of the Innovative Data Solutions’ Data Science team and will be responsible for providing thought leadership, applying statistical, advanced analytics, machine learning, and AI techniques to solve business problems. You will collaborate with a multi-disciplinary team of technical and non-technical business stakeholders on a wide range of challenges. You must understand the entire machine learning (ML) lifecycle, including problem framing, data collection, exploratory data analysis, model development, deployment, performance measurement, and business adoption.

Responsibilities:

• Support teams’ mission to partner with leaders across T-Mobile to understand the “art of the possible” and identify AI/ML opportunities to grow our business, reduce costs, manage risk, detect anomalous behavior, forecast/predict outcomes, and delight our customers
• Support business partners and product owners to understand business challenges, develop business cases, capture requirements, co-create solutions that drive business change that solve the challenges and deliver impactful business outcomes
• Provide senior-level guidance and mentorship to the data science team, including reviewing projects, models, and code for peers and junior team members.
• Design advanced analytical solutions to solve business problems; preprocess and perform exploratory data analysis on structured and unstructured data; create features based on expertise in the domain; use predictive modeling techniques and statistical analysis to predict outcomes and behaviors
• Leverage the Agile methodology to ensure alignment of data science roadmap, features, and stories to business priorities and value streams
• Collaborate with cross-functional team comprised of other data scientists, data engineers, ML engineers, and data analysts.
• Partner with other technology partners such as architects, engineers, product managers, scrum masters, release train engineers, and agile coaches to deliver on targeted business outcomes.
• Assist with the implementation, assessment and standardization of toolkits for our data science teams.

Skill Requirements:

• Excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest Algorithm, GBM, Naive Bayes, Support Vector Machines, Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short Term Memory (LSTM) networks, Transformers, etc.)
• Expertise in applying statistical, advanced analytics, machine learning, and/or AI, deep learning concepts, and techniques to solve business problems. Strong programming skills using Python, SQL, PySpark
• Expertise in one or more areas among Large Language Models (LLM), Transformers, Natural Language Processing (NLP), deep learning, recommender systems, and related fields is highly preferred.
• Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
• Strong analytical, critical-thinking skills with demonstrated ability to identify/analyze/synthesize data and use the data to drive decisions
• Superior communication and persuasion skills with executives and non-technical stakeholders, talent for storytelling, visualization, and creating insights from data to deliver practical recommendations for business action
• Good knowledge of calculus, linear algebra, statistics, and probability

Qualifications:

• Bachelor’s degree required, Master’s degree or Ph.D. preferred in Math, Statistics, Data Science, Analytics, Econometrics, Computer science, Operations Research, Behavioral Science, or another analytical/quantitative field required. 
• 7-10 years of industry experience in predictive modeling, data science, machine learning, AI, advanced analytics in a data scientist role, ML Scientist, research scientist, applied scientist or deep learning scientist role.
• 7-10 years of experience with programming languages like Python, PySpark, SQL, and/or R.
• Experience working with relational databases using SQL
• Experience with data querying, wrangling, cleaning, and feature engineering working with common relational and non-relational databases in big data environments such as Azure, AWS, or Google Cloud
• Experience articulating and translating business questions and using statistical techniques to arrive at an answer using data
• Experience writing and speaking about technical concepts to business, technical, and non-technical audiences and giving data-driven presentations
• Experience generating data-driven insights and explaining machine learning and analytical concepts to diverse audiences and multiple levels of leadership
• Experience with big data architecture and pipeline, such as Hadoop, Hive, Spark, and Kafka is a plus
• Experience in the telecom industry is a plus
• At least 18 years of age • Legally authorized to work in the United States

The pay range above is the general base pay range for a successful candidate in the state listed. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay may be above or below this range.

• Colorado Pay Range: $141,600.00 – $198,800.00
• Washington Range: $146,900.00 – $213,400.00
• California Range: $148,300.00 – $200,600.00
• New York Pay Range: $148,300.00 – $200,600.00

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 monthly bonuses based on individual and/or team performance, while Retail and Business Sales roles are eligible for monthly or quarterly sales incentives. And since we are ALL owners, EVERY employee at T-Mobile is eligible for an Annual Stock Grant. For information about T-Mobile’s amazing benefits, check outhttps://careers.t-mobile.com/culture-and-benefits/

Travel:

• Travel Required (Yes/No): Yes
• DOT Regulated:
• DOT Regulated Position (Yes/No): No
• Safety Sensitive Position (Yes/No): No

Never stop growing!

T-Mobile doesn’t have a corporate ladder–it’s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it’s that shared drive to aim high that drives our business and our culture forward.

If you’d like to receive more information about careers at T-Mobile, sign up for the T-Mobile Talent Community today!https://www.tmobile.careers/profile/join/

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.

Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the Los Angeles Fair Chance Initiative for Hiring Ordinance, we will consider for employment qualified applicants with arrest and conviction records.