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Koalafi

Checkout-integrated financing for merchants

Manager of Business Analytics - Fraud Ops Automation

AI Application EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree is required; a quantitative or technical field such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Data Science is preferred.
  • At least 5 years of experience in analytics, data science, business intelligence, or a related role in the fraud domain.
  • Strong proficiency in SQL and lightweight Python, with comfort working with large, unstructured datasets.
  • Hands-on fluency in building AI agents and LLM-based workflows to automate manual, judgment-heavy processes.
  • Experience building dashboards and visualizations in Tableau, Looker, Power BI, or similar tools.
  • Strong problem-solving skills, attention to detail, and ability to explain technical work to non-technical partners.

Responsibilities

  • Lead the design and build of AI agents and automated workflows that reduce manual effort across Fraud Operations.
  • Build and deploy AI agents that automate manual investigative processes, including merchant underwriting and real-time suspicious customer investigations.
  • Map investigative workflows end-to-end, identify high-value automation opportunities, and deliver solutions that reduce handle time and improve decision consistency.
  • Partner with Engineering, Data, and Fraud Strategy & Analytics to move AI and automation solutions from prototype to production in line with the company's AI strategy.
  • Establish guardrails, quality checks, and human-in-the-loop controls so automated decisions remain accurate, explainable, and auditable.
  • Deliver on-demand analysis on suspicious merchants and customers to support active investigations and escalations.
  • Proactively surface emerging fraud patterns, high-risk merchants, and linked customer activity before they become losses.
  • Build data-driven prioritization so investigators focus on the highest-risk cases first.
  • Support merchant monitoring with analytical deep dives that complement policies and models owned by Fraud Strategy & Analytics.
  • Design and maintain dashboards tracking investigator productivity, queue health, case outcomes, underwriting throughput, and fraud trends.
  • Replace manual, spreadsheet-based reporting with automated, reliable reporting.
  • Develop ad hoc reports for Fraud Operations leadership and cross-functional stakeholders.
  • Define and track operational KPIs such as time to decision, false positive rates, and investigator capacity.
  • Partner with Fraud Strategy & Analytics to translate front-line investigative findings into rule, policy, and model improvements, and ensure manual review aligns with policy intent.
  • Work with Product and Engineering to embed automation and data tools into case management and merchant update workflows, including JIRA.
  • Communicate findings to investigators, leadership, and partner teams, and help drive projects from idea to delivery.

Desired Qualifications

  • Familiarity with case management tools, JIRA, and workflow orchestration.
  • Experience with anomaly detection, entity resolution, or link analysis.
  • Experience in consumer finance, lending, lease-to-own, buy now, pay later (BNPL), payments, or fintech.

About the Company

Koalafi

Checkout-integrated financing for merchants

Koalafi provides pay-over-time financing integrated into a merchant’s checkout to simplify the purchase flow. It supports all credit types in a single application, helping nearly all customers qualify and boosting conversion and approval rates (over 90%). Revenue comes from financing fees and merchant partnerships, with the product embedded at the point of sale to manage multiple credit sources. The goal is to help merchants unlock new revenue opportunities and adapt to changing consumer buying habits through a seamless financing experience.

Company size
201-500
Company stage
Early VC
Total funding
$10.9M
Headquarters
Richmond, VA
Founded
2014

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