Data Scientists - Finance
T-Mobile
Location
🇺🇸 Bellevue, United States
Type
full_time
Salary
Undisclosed
Posted
2d ago
Job Description
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! 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. Data Scientists – Finance located in Bellevue, WA will prepare monthly and quarterly updates for existing models related to jump deferrals, Apple Forever Valuations, and Fair Market Value of Devices, and support the Modeling and Valuation team in adhoc data analytics. Position duties and
responsibilities
include, but are not limited to: • Operate the model, coordinate with stake holders, and run a process to estimate the liability associated with the Jump Program. • Update the Jump liability program to increase efficiency for various stakeholders. • Provide adhoc analytics on various valuations. • Perform data analytics and statistical analysis to support forecast of device values. • Provide data analytics and statistical analysis to support the estimate of the Apple Forever Liability. • Work with various stakeholders to prepare a model to forecast credit losses on T-Mobile service contracts. • Understand key data architecture and changes to the company to provide insights to various stakeholders with respect to data and valuation estimates. • Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week. • Minimal amount of travel for training or conferences may be required periodically. Skill
requirements
: • (1) Applying statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing to perform segmentation, prediction, forecast, and exploratory analysis; • (2) Extracting, integrating, and processing large-scale structured and unstructured datasets from multiple enterprise data warehouses and transactional databases using advanced SQL, Python and SAS. Performing data integrity checks to ensure completeness and accuracy under SOX compliance framework; • (3) Building and refining financial models to estimate the ASC 820 or IFRS 13 fair value of various assets and liabilities using US GAAP and IFRS compliant approaches by synthesizing data from internal systems, third-party market data, and historical financial performance; • (4) Performing fair value estimates of assets and liabilities using IFRS 13, IFRS 15, ASC460, ASC 606, ASC820, and ASC 805; and • (5) Interpreting and translating the results of statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing and accounting fair value estimates using ASC 460, ASC 606, ASC 820, and ASC 805 prepared by the data scientist into actionable insights for accounting leadership. Experience and