Sr Analysts, Credit Risk Mgmt

T-Mobile•Frisco, TX

10d•$105,500 - $115,000•Hybrid

About The Position

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. Sr Analysts, Credit Risk Management is located in Frisco, TX and will perform complex qualitative and quantitative analysis of credit policies to ensure financial goals are being attained. Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week. Less than 10% domestic travel to T-Mobile Headquarters is anticipated. No international travel anticipated.

Requirements

Bachelor’s degree or foreign equivalent in Finance, Economics, Mathematics, Analytics, Industrial Engineering, Statistics, or related, and 5 years of relevant work experience.
Master’s degree or foreign equivalent in Finance, Economics, Mathematics, Analytics, Industrial Engineering, Statistics, or related, and 3 years of relevant work experience.
Apply SQL, Python, Excel VBA and analytical programming language R to manipulate and analyze large-scale datasets, derive critical insights, and translate complex findings into clear, actionable recommendations tailored for Executive Leadership.
Utilize Snowflake SQL and Python to extract, transform, and integrate data from multiple sources, with knowledge in managing the full Exploratory Data Analysis (EDA) lifecycle, including advanced querying, data cleaning, feature engineering, and data profiling to ensure data quality and analytical accuracy.
Lead data-driven initiatives from requirements gathering to analytical framework design, with proficiency in leveraging statistical methods in R and Python including decision trees, regression models, and K-means clustering to enhance customer segmentation and credit risk strategies.
Develop executive-level visualizations and performance tracking dashboards using Tableau, Power BI, SQL, Excel VBA, and Python including pandas, matplotlib, and seaborn by performing ETL and data engineering including Extraction, Transformation, and Loading to deliver insights, monitor key metrics, and evaluate the impact of risk strategies.
Manage credit risk and underwriting by applying knowledge of credit structures and leveraging transactional data, external vendor data, and internal consumer behavioral data to build predictive, classification, and optimization models using Python and Excel.
Utilize Tableau and Power BI to visualize portfolio performance and support the design and implementation of new credit initiatives.
Develop financial models and forecasts: Customer Lifetime Value prediction, cohort analysis, scenario modeling, design of A/B experiments, using Excel, SQL, Python including NumPy, pandas, and scikit-learn to evaluate strategies and drive growth.
At least 18 years of age
Legally authorized to work in the United States

Responsibilities

Utilize statistical segmentation techniques to identify new opportunities.
Develop predictive financial and analytical models using appropriate statistical methodologies, including trend and regression analysis.
Participate and perform the analysis of new data and statistical products by external vendors.
Perform loss forecasting analysis.
Extract, process, and transform data from multiple disparate sources.
Analyzing credit bureau data and alternative credit data.