Credit Risk Management Analyst – Strategy

Jobtailor; Kansas; On-site; USD 65,000 - 90,000; Full time

Job summary

Jobtailor in Kansas seeks a quantitative credit analytics professional to drive segmentation, modeling, and policy optimization for wireless/telecom risk. You will work with Credit Risk Management and cross‑functional teams to deploy strategies and deliver actionable insights from large datasets.

Ideal candidates have 2–4 years in qualitative analytics, a finance/economics/math background, and strong SAS/SQL/Python/R skills. This role is full‑time, on-site in the United States.

Qualifications

• 2-4 years experience in a qualitative analytical function.
• Bachelor's degree in finance, economics, mathematics, stats or related field.
• Proficiency in SAS or other statistical/analytical languages.
• Strong Excel, Word and PowerPoint skills.
• Excellent written and verbal communication; strong organization.
• Time management and project management awareness.
• Must be legally allowed to work in the United States; 18+.
• Graduate degree is a plus; basic SQL/Python/R knowledge helpful.
• Prior consumer risk management experience a plus; telecom/wireless exposure a plus.

Responsibilities

• Utilize segmentation techniques to identify new opportunities.
• Extract, load and transform data from multiple sources for analysis.
• Develop predictive financial and analytical models using statistical methods.
• Analyze data and products from external vendors for insights.
• Collaborate with Credit Risk Management and other teams on deployment and tracking.
• Deliver outputs within project timelines and deadlines.
• Identify credit segmentation opportunities to improve decision processes.

Skills

Statistical Analysis

Trend Analysis

Regression Analysis

Data Transformation

Qualitative Analysis

Quantitative Analysis

SQL Proficiency

Python Proficiency

R Proficiency

Excel Proficiency

Education

Bachelor's Degree in Finance, Economics, Mathematics, Industrial Engineering, Statistics or related degree

Graduate degree in a quantitative discipline a plus

Tools

SAS

Excel

Word

PowerPoint

Statistical Software Packages

Job description

• Utilize statistical segmentation techniques to identify new opportunities
• Extract, load and transform data from multiple sources for statistical, reporting and ad-hoc analysis
• Perform qualitative and quantitative analysis of credit policies to meet objectives
• Develop predictive financial and analytical models using statistical methodologies, including trend and regression analysis
• Analyze new data and statistical products from external vendors
• Work with credit bureau and alternative credit data
• Deliver work output within project timelines and agreed-upon deadlines
• Identify credit segmentation opportunities to enhance credit decision processes, policies, collections strategies and fraud strategies
• Partner with Credit Risk Management and other T-Mobile functional teams on deployment, analysis and tracking of credit strategies
• Manipulate large datasets, extract insights and communicate actionable recommendations
• Participate in projects from hypothesis generation through development and implementation
• Contribute creative, credit-focused ideas and demonstrate problem-solving and ownership

Requirements

• 2-4 years experience in a qualitative analytical function
• Bachelor's Degree in Finance, Economics, Mathematics, Industrial Engineering, Statistics or related degree
• Intermediate or higher proficiency in SAS or other statistical/analytical programming languages
• Superior computer skills in Excel, Word, PowerPoint
• Superior communication (spoken and written), 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
• Graduate degree in a quantitative discipline a plus
• Basic proficiency in SQL, Python, R or other statistical software packages
• Prior consumer risk management experience a plus
• Wireless / Telecom experience a plus

Core Competencies

Demonstrates expertise in statistical analysis and data manipulation to drive credit decision processes and strategies. Proficient in developing predictive models and collaborating with cross-functional teams to enhance credit risk management.

Highest-signal resume keywords

• Statistical Segmentation Techniques
• Predictive Financial Modeling
• SAS Proficiency
• Credit Risk Management
• Data Analysis

ATS Optimization Keywords

Hard Skills

• Statistical Analysis
• Trend Analysis
• Regression Analysis
• Data Transformation
• Qualitative Analysis
• Quantitative Analysis
• SQL Proficiency
• Python Proficiency
• R Proficiency
• Excel Proficiency

Soft Skills

• Communication Skills
• Organizational Skills
• Presentation Skills
• Time Management Skills
• Problem-Solving Skills

Industry Keywords

• Credit Policies
• Consumer Risk Management
• Wireless
• Telecom
• Credit Segmentation

Tools & Technologies

• SAS
• Excel
• Word
• PowerPoint
• Statistical Software Packages