Principal Data Scientist, Consumer Group

at  TMobile USA Inc

BE UNSTOPPABLE WITH US!

T-Mobile is synonymous with innovation–and you could be part of the team that disrupted an entire industry! We reinvented customer service, brought real 5G to the nation, and now we’re shaping the future of technology in wireless and beyond. Our work is as exciting as it is rewarding, so consider the career opportunity below as your invitation to grow with us, make big things happen with us, above all, #BEYOU with us. Together, we won’t stop!
Job Overview
The Principal Data Scientist is responsible for leading technical innovation within the data science team. The Principal Data Scientist collaborates with a multi-disciplinary team of technical and non-technical business stakeholders on a wide range of challenges and develops the next generation of advanced analytics and Machine Learning (ML) modeling products and solutions. The Principal Data Scientist is 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 mastery of 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.

Job Responsibilities:

• Extract, prepare, and model large, complex data sets using a combination of skills, including machine learning theory, mathematics, statistics, and programming.
• Identify critical and emerging technologies that will support and extend our consumer data, data integration, and quantitative analytic capabilities.
• Lead the implementation, assessment and standardization of advanced analytics and modeling toolkits for our data science teams.
• Partner with data engineering teams to shape data management strategies, architecture, governance, pipelines, and infrastructure enabling effective modeling environments for data science teams.
• Apply language models (NLP/LLM) to provide customer contact insight and answer business questions.
• Provide senior level guidance 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.

Education:

• Bachelor’s Degree Quantitative Subject area (math, statistics, economics, computer science, physics, engineering) (Required)
• Master’s/Advanced Degree Quantitative Subject area (math, statistics, economics, computer science, physics, engineering) (Preferred)

Work Experience:

• 7-10 years 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 (Required)
• 4-7 years Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations (Required)
• 7-10 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
• 4-7 years Experience with statistical methods and advanced modeling techniques. For example- SVM, Random Forest, graph models, Bayesian inference, neural networks, NLP, LLM (Required)
• 4-7 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, etc. (Required)
• 7-10 years Experience with data scripting languages (e.g., SQL, Python, R) (Required)
• 4-7 years Experience in data visualization (Required)
• 7-10 years Extended experience working with relational database using SQL (Required)
• 1-3 years Experience in implementing and deploying LLMs in a production environment (Preferred)
• 4-7 years Experience in telecom industry (Preferred)

Knowledge, Skills and Abilities:

• Mathematics Calculus, linear algebra, statistics, and probability (Required)
• Programming Mastery of Python and SQL (Required)
• Machine Learning: Apply machine learning techniques including supervised and unsupervised learning; collaborative filtering; and artificial neural networks (Required)
• Deep Learning: Research, design, implement, evaluate, and optimize novel algorithms/models in Deep Learning space (Required)
• LLM prompt engineering and techniques
• Communication Exemplary communication skills, ability to work with cross functional teams (Required)
• At least 18 years of age
• Legally authorized to work in the United States

• Extract, prepare, and model large, complex data sets using a combination of skills, including machine learning theory, mathematics, statistics, and programming.
• Identify critical and emerging technologies that will support and extend our consumer data, data integration, and quantitative analytic capabilities.
• Lead the implementation, assessment and standardization of advanced analytics and modeling toolkits for our data science teams.
• Partner with data engineering teams to shape data management strategies, architecture, governance, pipelines, and infrastructure enabling effective modeling environments for data science teams.
• Apply language models (NLP/LLM) to provide customer contact insight and answer business questions.
• Provide senior level guidance 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