Data Analyst

QCHI / LendNation is hiring an experienced Data Analyst for its Marketing team. The role leads end-to-end analytics projects in lending, credit risk, fraud, and marketing, partnering with underwriting, marketing, product, and external vendors to inform strategy and improve portfolio performance.

Responsibilities:

• This role owns analytic projects end-to-end: defining objectives, extracting and validating data, performing analysis, presenting findings, and ensuring recommendations are adopted
• The individual will partner with underwriting, marketing, product, and external vendors to quantify risk, identify growth opportunities, and improve portfolio performance
• Success in this role means translating complex analysis into clear, persuasive recommendations that directly influence strategy, decisioning, and financial outcomes

Requirements:

• This is an experienced Data Analyst who can independently drive high-impact analysis and shape strategic decisions
• The ideal candidate brings proven experience in online lending analytics, fraud detection, and credit risk performance management—preferably in subprime or alternative financial services
• Experienced in credit and fraud analytics, not just reporting
• Able to challenge assumptions and propose analytical solutions
• Self-directed, accountable, and comfortable prioritizing multiple workstreams
• 5+ years analytics experience in online lending, fintech, consumer credit, fraud, or related industry
• 5+ years hands-on experience using R or Python for data extraction, modeling, automation, and analysis
• Credit risk analysis, segmentation, and underwriting decision support
• Fraud detection analytics (velocity checks, behavioral/identity risk indicators)
• Portfolio performance measurement and optimization
• Online marketing analytics and customer lifecycle performance
• Strong SQL skills, including SAS
• Ability to communicate insights visually and verbally to both technical and non-technical audiences (Power BI, Tableau, etc.)
• Proven ability to drive outcomes and influence leadership through data-based recommendations