Sr Analysts, Credit Risk Mgmt

At T-Mobile, we invest in you with a comprehensive Total Rewards Package that includes a competitive base salary and multiple wealth-building opportunities such as an annual stock grant, employee stock purchase plan, 401(k), and free year-round money coaching.

About the role

This position is located in Frisco, TX and involves performing complex qualitative and quantitative analysis of credit policies to ensure financial goals are met. Telecommuting is permitted, but the 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, with no international travel expected.

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 in and perform analysis of new data and statistical products by external vendors.
• Perform loss forecasting analysis.
• Extract, process, and transform data from multiple disparate sources.
• Analyze credit bureau data and alternative credit data.
• 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 for Executive Leadership.
• Utilize Snowflake SQL and Python for data extraction, transformation, and integration, managing the full Exploratory Data Analysis (EDA) lifecycle, including advanced querying, data cleaning, feature engineering, and data profiling.
• Lead data-driven initiatives from requirements gathering to analytical framework design, leveraging statistical methods in R and Python, such as 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.
• 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, including Customer Lifetime Value prediction, cohort analysis, scenario modeling, and design of A/B experiments using Excel, SQL, Python (including NumPy, pandas, and scikit-learn) to evaluate strategies and drive growth.

Requirements

Education and Experience:

• Primary Requirements: Bachelor’s degree or foreign equivalent in Finance, Economics, Mathematics, Analytics, Industrial Engineering, Statistics, or related field, and 5 years of relevant work experience.
• Alternative Requirements: Master’s degree or foreign equivalent in Finance, Economics, Mathematics, Analytics, Industrial Engineering, Statistics, or related field, and 3 years of relevant work experience.

Skills

• Experience applying SQL, Python, Excel VBA, and R to manipulate and analyze large-scale datasets, derive insights, and translate findings into actionable recommendations.
• Proficiency in Snowflake SQL and Python for data extraction, transformation, and integration, including managing the full EDA lifecycle.
• Ability to lead data-driven initiatives from requirements gathering to analytical framework design using statistical methods in R and Python (e.g., decision trees, regression models, K-means clustering).
• Experience developing executive-level visualizations and dashboards using Tableau, Power BI, SQL, Excel VBA, and Python (pandas, matplotlib, seaborn).
• Knowledge of credit risk and underwriting, including building predictive, classification, and optimization models using Python and Excel.
• Experience developing financial models and forecasts, including Customer Lifetime Value prediction, cohort analysis, and scenario modeling using Excel, SQL, and Python (NumPy, pandas, scikit-learn).

Pay

Salary range: $105,500 to $115,000 per year. The successful candidate’s actual pay will be based on work location, qualifications, and experience.

Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance, set as a percentage of eligible earnings. Certain positions may also be eligible for monthly or quarterly bonuses or sales incentives.

Benefits

• Comprehensive medical, dental, and vision insurance.
• Flexible spending account.
• 401(k) retirement plan.
• Annual stock grant and employee stock purchase plan.
• Paid time off and up to 12 paid holidays (approximately 4 weeks for new full-time employees and 2.5 weeks for new part-time employees annually).
• Paid parental and family leave.
• Family building benefits, back-up care, enhanced family support, and childcare subsidy.
• Tuition assistance and college coaching.
• Short- and long-term disability coverage.
• Voluntary AD&D, accident, life, disability, and long-term care insurance.
• Mobile service and home internet discounts.
• Pet insurance.
• Commuter and transit programs.

Location: Frisco, TX. Work hours: 40 hours per week.