Merchant Risk Data Analyst

Atlantafull timeRemote

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mid

H1B: yes

Upgrade Merchant Risk Data Analyst at Upgrade analyzes transactional data to identify and mitigate merchant risk through predictive modeling and automated triggers. The role involves building dashboards and collaborating with Engineering and Product teams to operationalize risk monitoring.

Responsibilities

Upgrade is looking for a Merchant Risk Data Analyst to transform how we identify and mitigate merchant risk through data analysis and visualization. You'll combine merchant risk expertise with analytical skills to build predictive models, automated monitoring triggers, and actionable insights that protect our platform from fraud, compliance violations, and operational failures. You'll turn millions of transactional data points into strategic risk decisions, applying analytical rigor to catch problems early and safeguard our merchants, borrowers, and business.
Analyze large volumes of transactional data to identify merchant risk patterns and trends
Build predictive models to forecast merchant fraud, financial distress, compliance issues, and operational red flags
Develop risk scoring methodologies that prioritize high-risk merchants for proactive review
Conduct historical trend analysis to understand how merchant risk evolves over time and across verticals
Identify leading indicators of merchant misconduct, project abandonment, chargebacks, and borrower harm
Design automated merchant risk triggers based on transactional behavior and performance metrics
Create early-warning systems for financial distress, fraud patterns, compliance violations, and operational deterioration
Optimize trigger logic to balance detection accuracy with operational efficiency
Collaborate with Engineering and Product to operationalize triggers into monitoring workflows
Monitor trigger performance and adjust thresholds based on investigation outcomes
Build and maintain Tableau dashboards for merchant investigations using transactional data, WIP trends, chargeback patterns, and complaint analysis

Qualification

Knowledge of merchant underwritingBackground in home improvement

Preferred

Experience with Python or R for data analysis and modeling
Familiarity with machine learning techniques and model validation
Knowledge of merchant underwriting, credit risk, or transaction monitoring
Experience with WIP (Work-in-Progress) data in project-based lending
Background in home improvement, solar, elective medical, or other merchant verticals
Understanding of regulatory requirements (UDAAP, state licensing, consumer protection)
Prior experience building automated alerting systems or risk triggers