At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees!
Ready to elevate your career and be a part of the Uncarrier journey at T-Mobile?Our team is searching for a Principal Data Scientist responsible for leading technical innovation within our data science team. We collaborate with a multi-disciplinary team of technical and non-technical business partners on a wide range of challenges and develops the next generation of advanced analytics and Machine Learning (ML) modeling products and solutions. You'll be entrusted with developing the Artificial Intelligence (AI) that drives the most important aspects of the business. This position is at the forefront of new AI technologies and represents proficiency in existing machine learning techniques. Paramount to this job is the understanding that a Principal Data Scientist is a forward-thinking individual contributor that helps define the long-term technical vision of the data science teams within T-Mobile.
We pride ourselves on encouraging a culture of innovation, advocating for agile methodologies, and promoting transparency in all that we do. Join us in embodying the spirit of the 'Un-carrier' and make a tangible impact! If you are passionate about driving perfection and want to make a significant impact, apply today!
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
- Identify critical and new technologies that will support and extend our consumer data, data integration, and quantitative analytic capabilities.
- Scale and own the implementation, assessment and standardization of advanced analytics and modeling toolkits for our data science teams.
- Partner with data and machine learning engineering teams to craft data management strategies, architecture, governance, pipelines, and infrastructure enabling effective modeling environments for data science teams
- Provide senior level mentorship to the data science and measurement science teams on approach and methodologies
- Communicate important information and insights to business leaders using verbal, written, and data visualization skills.
KNOWLEDGE, SKILLS AND ABILITIES:
- 7+ years Proven experience in predictive modeling, data science, and analysis in a data scientist, research scientist, applied scientist, ML scientist or engineer role building and deploying ML models or hands on experience developing deep learning or large language models
- 7+ years demonstrated ability writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations while articulating and translating business questions and using statistical techniques to arrive at an answer using available data
- 7+ years demonstrated ability with statistical methods and sophisticated machine and deep learning modeling techniques. For example - Linear Regression, Logistic Regression, Clustering/Segmentation, Bayesian inference, NLP, Large Language Models, Gen AI, Decision Tree, Random Forest Algorithm, GBM, Naive Bayes, Support Vector Machine, and Neural Networks, etc.
- 7+ years proven experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. coupled with validated ability with data scripting languages (e.g., Python, R) and relational database using SQL
- 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.
- Experience with CI/CD pipelines, training, retraining, influencing, and monitoring complex ML algorithms in production environment.
- Mathematics Calculus, linear algebra, statistics, and probability
- Outstanding communication skills, ability to work with multi-functional teams
EDUCATION:
- Bachelor's Degree Quantitative Subject area (math, statistics, economics, computer science, physics, engineering)
- PhD/Master's (math, statistics, economics, computer science, physics, engineering) (Preferred)
• At least 18 years of age
• Legally authorized to work in the United States
Travel:
Travel Required (Yes/No):No
DOT Regulated:
DOT Regulated Position (Yes/No):No
Safety Sensitive Position (Yes/No):No
The pay range above is the general base pay range for a successful candidate in the role. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.
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. To find the pay range for this role based on hiring location, https://paylookup.t-mobile.com/paylookup?reqID=REQ299280¶dox=1At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile’s amazing benefits, check out www.t-mobilebenefits.com.
Never stop growing!
As part of the T-Mobile team, you know the Un-carrier 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. By applying for this career opportunity, you’re living our values while investing in your career growth–and we applaud it. You’re unstoppable!
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.
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