Koalafi - Manager of Business Analytics, Fraud Ops Automation

• AI-Driven Workflow Automation • Build and deploy AI agents that automate manual investigative processes, including merchant underwriting and real-time suspicious customer investigations. • Map current investigative workflows end-to-end, identify the highest-value automation opportunities, and deliver solutions that measurably 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 Koalafi's long-term AI strategy. • Establish guardrails, quality checks, and human-in-the-loop controls so automated decisions remain accurate, explainable, and auditable. • Investigative Insights & Proactive Detection Give Fraud Operations on-demand and proactive visibility into suspicious activity. • Investigative Insights & Proactive Detection • 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 the policies and models owned by Fraud Strategy & Analytics. • Operational Reporting & Dashboards Build the reporting backbone for Fraud Operations. • Operational Reporting & Dashboards • 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. • Cross-Functional Partnership Serve as the bridge between Fraud Operations and Koalafi's analytics, product, and technology teams. • Cross-Functional Partnership • Partner with Fraud Strategy & Analytics to translate front-line investigative findings into rule, policy, and model improvements, and to 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 clearly to investigators, leadership, and partner teams, and help drive projects from idea to delivery. • Bachelor's degree required, preferably in a quantitative or technical field such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Data Science. • At least 5 years of experience in analytics, data science, business intelligence, or a related role in Fraud domain. • At least 5 years • in Fraud domain • Strong proficiency in SQL and lightweight Python; comfortable working with large, unstructured datasets. • Strong proficiency in SQL • Hands-on fluency in building AI agents and LLM-based workflows (for example, using frameworks and APIs from leading AI providers) to automate manual, judgment-heavy processes. • Hands-on fluency in building AI agents • Experience building dashboards and visualizations in tools such as Tableau, Looker, Power BI, or similar. • Experience building dashboards and visualizations • A builder's mindset: you get excited about finding manual processes and automating them. • A builder's mindset: • Strong problem-solving skills, attention to detail, and the ability to explain technical work to non-technical partners.