Senior Data Analyst @ Progressive Leasing
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About the Senior Data Analyst Role
Progressive Leasing is a leading provider of in-store and e-commerce lease-to-own solutions. This nearly 20+ year old FinTech company has evolved from a start-up to an industry leader by innovating and simplifying consumer finance. As a subsidiary of PROG Holdings (NYSE: PRG), Progressive Leasing is part of an exciting FinTech holding company with multiple business segments.
The Role
The Senior Data Analyst will use advanced data mining techniques, interactive data visualizations, and statistical models to uncover business insights from transactional and unstructured data. You will work with tools such as R, Python, Tableau, Power BI, and SQL to ensure data driven decision making.
Key Responsibilities
- Create interactive data visualizations to monitor performance and market trends.
- Build and run models for optimal resource allocation.
- Analyze transactional data to detect and prevent fraud.
- Extract actionable insights from unstructured data using advanced data mining techniques.
Who You Are
You are a driven analytics professional with strong quantitative skills and a track record in creative problem solving. You have experience using data mining and visualization tools and a deep understanding of business impacts drawn from data.
What We Offer
- Competitive Compensation and full health benefits.
- Opportunities for advancement into data science or leadership tracks.
- Employee stock purchase program and tuition reimbursement.
- Paid Time Off, Holidays, and Volunteer Hours.
- A diverse and inclusive work environment.
Key skills/competency
Data Mining, Visualization, SQL, Python, R, Tableau, Power BI, Analysis, FinTech, Fraud Prevention
How to Get Hired at Progressive Leasing
🎯 Tips for Getting Hired
- Customize your resume: Tailor details to data analytics skills.
- Highlight technical skills: Emphasize SQL, Python, R, and BI tools.
- Research Progressive Leasing: Understand their FinTech evolution and values.
- Prepare for behavioral interviews: Be ready with concrete data examples.