Merchant Risk Data Analyst

Upgrade•Atlanta, GA

About The Position

Upgrade is seeking a Merchant Risk Data Analyst to use data analysis and visualization to improve how merchant risk is identified and mitigated. The role combines merchant risk expertise with analytical skills to build predictive models, automated monitoring triggers, and actionable insights that help protect the platform from fraud, compliance violations, and operational failures. The analyst will turn transactional data into risk decisions that help identify problems early and safeguard merchants, borrowers, and the business. The analyst will build and maintain Tableau dashboards and reporting for investigations, team productivity, investigation outcomes, risk mitigation effectiveness, merchant risk trends, and portfolio health. The position works closely with Merchant Risk colleagues and cross-functional partners, including Engineering, Product, Sales, Credit, Compliance, and FinCrimes, to improve risk detection and operationalize monitoring workflows. Work may take place in a contact center, office, or remote environment depending on business needs and the nature of the role.

Requirements

At least 3 years of merchant risk experience in fraud detection, compliance monitoring, underwriting, or risk operations; fintech, payments, or lending experience is preferred.
Strong SQL skills for querying large datasets and performing complex data analysis.
Proficiency in Tableau or similar BI tools for building dashboards and visualizations.
Experience with predictive modeling and statistical analysis, including regression, classification, and clustering.
Expertise in Excel or Google Sheets for data manipulation, pivot tables, and analysis.
Deep merchant risk knowledge, including fraud patterns, financial distress indicators, compliance red flags, operational issues, and borrower harm signals.
Analytical mindset, strong attention to detail, and ability to identify patterns in complex data.
Clear communication skills to translate analytical findings for non-technical audiences.

Nice To Haves

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 such as UDAAP, state licensing, and consumer protection.
Prior experience building automated alerting systems or risk triggers.

Responsibilities

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 to prioritize high-risk merchants for proactive review.
Conduct historical trend analysis to understand how merchant risk changes 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 in 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.
Create visualizations that help the Merchant Risk team investigate merchants quickly and effectively.
Develop performance metrics reporting for team productivity, investigation outcomes, and risk mitigation effectiveness.
Design executive-level reporting on merchant risk trends and portfolio health.
Ensure dashboards are intuitive, accurate, and actionable.
Partner with Merchant Risk Managers and analysts to understand investigation needs and data gaps.
Provide data-driven recommendations to improve risk detection and investigation efficiency.
Collaborate with Sales, Credit, Compliance, FinCrimes, and Product teams on risk strategy.
Present findings and recommendations to leadership in clear, compelling formats.
Stay current on merchant risk trends, fraud schemes, and industry best practices.