Lead Merchant Risk Analyst
$120.8k - $169.1kWisetack
Lead Merchant Risk Analyst
Remote, USA
Wisetack connects contractors and consumers through home services financing — and trust on both sides of that marketplace depends on effectively identifying and managing risk.
We're looking for a Lead Merchant Risk Analyst to help shape how we detect, investigate, and respond to merchant fraud across the merchant lifecycle. This is a senior individual contributor role that combines deep analytical work with opportunities to improve risk processes, monitoring, and decisioning at scale.
You'll work closely with Risk, Product, Data Science, Data Engineering, Compliance, and Operations to identify emerging threats, strengthen controls, and support safe growth for merchants and consumers.
As Wisetack continues to invest in automation and AI-powered workflows, you'll have the opportunity to help design and improve systems that make risk operations more scalable and effective.
Responsibilities
- Lead analytical work across the merchant risk lifecycle, including onboarding, KYB/KYC, transaction monitoring, and merchant decisioning
- Build and maintain queries, dashboards, alerts, and reporting that identify fraud patterns, emerging risks, and control gaps
- Investigate high-risk merchant activity, including business misrepresentation, suspicious transactions, inflated invoices, collusion, refund abuse, and account takeover
- Translate findings into clear recommendations that improve risk controls, merchant experience, and business outcomes
- Measure the impact of rule changes, segmentation strategies, and risk experiments on fraud losses, approval rates, false positives, and customer experience
- Partner with Data Science, Data Engineering, and third-party vendors to evaluate risk signals, models, data quality, and monitoring infrastructure
- Contribute to the development of scalable monitoring, decisioning, and automation capabilities, including AI-enabled workflows where appropriate
- Help identify emerging merchant fraud trends and opportunities to strengthen Wisetack's risk strategy
Requirements
- Bachelor's degree in a quantitative field (math, economics, statistics, data science, finance, engineering) or equivalent practical experience
- 5+ years of experience in fraud, merchant risk, payments risk, or financial services analytics
- Strong SQL proficiency and experience using Python, R, SAS, or similar tools to analyze complex datasets and generate actionable insights
- Experience working with risk models, machine learning outputs, or rules-based strategies to detect fraud and emerging risk trends
- Familiarity with merchant onboarding, KYB/KYC, identity verification, business verification, sanctions screening, firmographic data, or fraud vendor integrations
- Experience collaborating with Data Science and Data Engineering teams to develop scalable risk monitoring and decisioning capabilities
- Strong communication, ownership, and judgment, with the ability to balance fraud prevention, merchant experience, consumer protection, compliance, and growth
- Experience using AI tools, automation, or workflow optimization to improve analytical or operational efficiency is a plus
Bonus Points
- Fintech experience
- Experience supporting consumer lending products
- Experience building dashboards, automated monitoring, or operational workflows
- Experience evaluating or implementing AI-powered tools and automation solutions
Conclusion
The range of base salary for the position is between $120,800.00 - $ 169,100.00, plus equity, and benefits. Please note that the base salary range is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level and competencies.
Spend a little time on our About Us page and check out our Press page and our blog for more. If you think this might be a fit, we'd love to hear from you!
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making. Our data practices are described in Wisetack's Privacy Policy.
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