Senior Data Scientist

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! Job Overview This position is not eligible to sponsor an immigration visa. This is a hybrid role that must be in the Bellevue WA office 3 days per week. Advertising, meet the Un-carrier. T-Mobile Advertising Solutions (T-Ads) is standing up for Consumers and Advertisers to redefine an industry. Again. Ever feel like relevant, engaging, and safe advertising is an impossible ask? We are working to change that by building an advertising platform that allows brands and advertising agencies to engage real audiences with a customer centric, privacy first approach. T-Ads is a small, fast paced team of master generalists. The T-Ads data science team builds data products for T-Ads. Our projects range from crafting ML models to predict demographics or app engagement to large data aggregations to generate app insights to custom analyses on unique first party data. Members of our team are ready to apply the latest modeling techniques, advanced statistics and math and data manipulation to any complex problem thrown our way. We are looking for team members who can critically analyze a problem, collaborate with product management to find a solution, and lead the delivery of that solution to the end customer. You must be able to work across the entire machine learning (ML) lifecycle, including problem framing, data collection, exploratory data analysis, model development, deployment, and performance measurement. Paramount to this job is the understanding that a data scientist's ultimate goal is to build real business value from data. This is an opportunity to work on multiple products used by a variety of end users such as the major advertising agencies and brands in the United States. Job Responsibilities: Lead data science projects independently by identifying and planning work, making basic project decisions and resolving issues. Provide senior-level guidance and mentorship to the data science team, including reviewing projects, models, and code for peers and junior team members. Communicate optimally with a technical and non-technical audience using verbal, written, and data visualization skills. Work with the business to understand real-world, vague or sophisticated business problems and translate them into machine learning or data aggregation problems and tackle them by crafting efficient data products. Liaise with data source owners to understand available datasets and identify valuable data sources for business problems. Collaborate with cross-functional team comprised of other data scientists, data engineers, ML engineers, and data analysts to craft and deploy products. Clean, validate and pre-process structured and unstructured data from multiple, sophisticated datasets. Perform exploratory data analysis (EDA) and custom analysis on sophisticated datasets using advanced statistics and math. Build sophisticated data aggregations that persist in data stores that meet statistical significance thresholds and are debiased and scaled according to business requirements. Design, develop, deploy, monitor and maintain scalable data pipelines required to support derivative datasets used in data products. Design, feature engineer, train, tune and test ML models to solve sophisticated data problems including predicting outcomes using the latest ML libraries and tools. Design, develop, deploy, monitor, retrain and maintain ML pipelines that support ML models built for data products. Train ML models and manipulate large datasets using bi