Analyst, Credit Risk Management – Strategy

T-Mobile

. Identify new credit segmentation opportunities using statistical methods .

Posted 10/26/2026full-timeUnited StatesJuniorMid-Level💰 $76,100 - $137,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical methods for credit segmentation, data manipulation, and predictive modeling. Proficient in utilizing programming languages and data visualization tools to analyze and communicate actionable insights effectively.

Highest-signal resume keywords

Statistical Segmentation TechniquesPredictive Financial ModelingSQL Data Extraction and TransformationData Visualization with TableauCredit Risk Management Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical MethodsPredictive ModelingData AnalysisRegression ModelsK-Means ClusteringSQLRPythonExcel VBATrend Analysis

Soft Skills

Communication SkillsOrganizational SkillsPresentation SkillsTime Management Skills

Tools & Technologies

TableauPower BIExcelSASPython Libraries (Pandas, Matplotlib)

Industry Keywords

Credit Risk ManagementConsumer Risk ManagementWireless/Telecom ExperienceQuantitative AnalysisFinancial Analysis

Tech Stack

Tools & technologies

PandasPythonSQLTableauVBA

About the role

Key responsibilities & impact

Identify new credit segmentation opportunities using statistical methods
Enhance credit decision processes and policies, collections strategies, and fraud strategies
Partner with Credit Risk Management and other T-Mobile functional teams to deploy, analyze, and track credit strategies
Manipulate large amounts of data and extract key insights
Communicate actionable recommendations based on data analysis
Participate in projects from hypothesis generation through development and implementation
Utilize statistical segmentation techniques such as decision trees, regression models, and K-means clustering
Extract, load, and transform data from multiple sources using SQL, Excel VBA, R, Python, and other tools
Perform qualitative and quantitative analysis of credit policies
Develop predictive financial and analytical models using trend and regression analysis
Analyze new data and statistical products from external vendors
Work with credit bureau and alternative credit data
Deliver work according to project timelines and agreed deadlines

Requirements

What you’ll need

Bachelor's Degree plus 2 years of related work experience OR combination of education and experience deemed equivalent
Intermediate or higher proficiency in SAS, SQL, R, Python, or other statistical/analytical programming languages
Familiarity with data visualization tools including Tableau, Power BI, SQL, Excel/VBA, Python including pandas and matplotlib
Superior computer skills in Excel, Word, and PowerPoint
Superior spoken and written communication, organization, and presentation skills
Superior time management skills and awareness of project management methods
At least 18 years of age
Legally authorized to work in the United States
Preferred: Graduate degree in a quantitative discipline
Preferred: 3+ years of quantitative analytic modeling experience, credit risk management or comparable process management experience
Preferred: Finance, Economics, Mathematics, Industrial Engineering, Statistics, or related degree
Preferred: Prior consumer risk management experience
Preferred: Wireless/Telecom experience

Benefits

Comp & perks

Annual stock grant
Employee stock purchase plan
401(k)
Free, year-round money coaches
Medical, dental and vision insurance
Flexible spending account
Paid time off
Up to 12 paid holidays
Paid parental and family leave
Family building benefits
Back-up care
Enhanced family support
Childcare subsidy
Tuition assistance
College coaching
Short- and long-term disability
Voluntary AD&D coverage
Voluntary accident coverage
Voluntary life insurance
Voluntary disability insurance
Voluntary long-term care insurance
Mobile service and home internet discounts
Pet insurance
Commuter and transit programs
Career growth opportunities