Manager of Business Analytics, Fraud Ops Automation

New

KoalafiConsumer finance

Remote (U.S.). Remote opportunities are available to candidates throughout the United States.Full-TimeManager

Salary$128,000-$165,000 per year (depending on experience and location)

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Job Details

Experience: At least 5 years of experience in analytics, data science, business intelligence, or a related role in Fraud domain.
Required Skills: PythonSQLMicrosoft Power BIJiraTableauLooker

Hold a bachelor’s degree; a quantitative or technical field such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Data Science is preferred.
Have at least 5 years of experience in analytics, data science, business intelligence, or a related role in the fraud domain.
Demonstrate strong proficiency in SQL.
Be comfortable using lightweight Python and working with large, unstructured datasets.
Have hands-on fluency building AI agents and LLM-based workflows to automate manual, judgment-heavy processes.
Have experience building dashboards and visualizations in Tableau, Looker, Power BI, or similar tools.
Bring a builder’s mindset and interest in identifying and automating manual processes.
Have strong problem-solving skills and attention to detail.
Be able to explain technical work to non-technical partners.
Familiarity with case management tools, JIRA, and workflow orchestration is a plus.
Experience with anomaly detection, entity resolution, or link analysis is a plus.
Experience in consumer finance, lending, lease-to-own, BNPL, payments, or fintech is a plus.

Design and build AI agents and automated workflows to reduce manual effort across Fraud Operations.
Automate investigative processes, including merchant underwriting and real-time suspicious customer investigations.
Map investigative workflows, identify automation opportunities, and deliver solutions that reduce handle time and improve decision consistency.
Establish guardrails, quality checks, and human-in-the-loop controls for accurate, explainable, and auditable automated decisions.
Analyze suspicious merchants and customers to support investigations and escalations.
Surface emerging fraud patterns, high-risk merchants, and linked customer activity, and build data-driven case prioritization.
Design and maintain dashboards for investigator productivity, queue health, case outcomes, underwriting throughput, and fraud trends.
Replace manual spreadsheet-based reporting with automated reporting and develop ad hoc reports for leadership and stakeholders.
Define and track operational KPIs, including time to decision, false positive rates, and investigator capacity.
Partner with Fraud Strategy & Analytics, Product, Engineering, and Data to improve policies, models, case management, and merchant update workflows.

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