Strategic Fraud Intelligence Analyst

Description BioCatch is the leader in Behavioral Biometrics, a technology that leverages machine learning to analyze an online user’s physical and cognitive digital behavior to protect individuals online. BioCatch’s mission is to unlock the power of behavior and deliver actionable insights to create a digital world where identity, trust, and ease coexist. Today, 34 of the world's largest 100 banks and 210 total financial institutions rely on BioCatch Connect™ to combat fraud, facilitate digital transformation, and grow customer relationships.. BioCatch’s Client Innovation Board, an industry led initiative including American Express, Barclays, Citi Ventures, and National Australia Bank, helps BioCatch to identify creative and cutting edge ways to leverage the unique attributes of behavior for fraud prevention. With over a decade of analyzing data, more than 80 registered patents, and unparalleled experience, BioCatch continues to innovate to solve tomorrow’s problems. For more information, please visit www.biocatch.com. We are expanding our Fraud Intelligence Unit and need passionate, sales-focused, fraud fighters to join our team. Reporting to the Global Fraud Intelligence Director, you will be responsible for conducting deep-dive, targeted analysis of fraud patterns to support high-impact, engagement strategies for prospective customers, with the goal of supporting the sales team and business in securing revenue growth. Unlike broader trend analysis roles within the team, this position focuses on generating highly tailored insights for a defined set of priority prospects, helping articulate the need for BioCatch’s advanced fraud and financial crime prevention solutions. You will work closely with internal stakeholders to analyse BioCatch and external data with a hypothesis-driven approach, uncovering specific vulnerabilities, attack patterns, and risk exposures relevant to individual organisations or segments. Your work will translate complex data into compelling, evidence-based narratives that highlight both the impact of fraud and the urgency of addressing it. Key responsibilities: Support the Sales team in the generation and progression of revenue-generating opportunities. Conduct deep, targeted analysis of BioCatch data to identify customer- or segment-specific fraud patterns, risks, and vulnerabilities. Apply advanced analytical techniques and hypothesis-driven investigation to uncover insights that are not visible through high-level trend analysis. Leverage AI-assisted analytical tools to enhance the scale and speed of analysis, while applying rigorous data validation and expert judgment to ensure accuracy and relevance. Translate analytical findings into tailored, prospect-relevant narratives that clearly articulate fraud exposure, business impact, and the value of mitigation strategies. Develop insight-driven materials that support commercial engagement, including customer-specific briefings, strategic reports, and pre-sales narratives. Collaborate closely with sales, marketing, and regional teams to align analytical tasks with customer priorities and commercial objectives. Design and develop effective data visualisations that simplify complex findings and strengthen the impact of customer-facing storytelling. Present findings internally as well as directly to customers, demonstrating credibility through data-backed insights and clear articulation of fraud risks. Build and maintain analytical frameworks, datasets, and repeatable methodologies that support scalable customer-focused analysis. Identify opportunities to enhance analytical workflows through automation and AI, while ensuring critical thinking and professional judgment guide all conclusions. Stay current with emerging fraud trends, analytical techniques, and AI capabilities, applying them to continuously improve the precision and impact of insights. Requirements A bachelor’s/master’s degree in a STEM field and/or self-directed technology-focused education in data analytics or programming. Experience in fraud, financial crime, data analysis, or a related field (banking experience advantageous but not essential depending on analytical strength). Strong SQL skills (intermediate to advanced). Experience with Python and/or R (strongly advantageous). Hands-on experience with AI tools to support research and analysis, with a clear understanding of their capabilities, limitations, and associated risks. Strong analytical skills with the ability to work with complex, large-scale datasets and extract actionable insights. Strong written and verbal communication skills, with the ability to translate technical findings into clear, commercially relevant narratives. Experience in delivering effective messages to executive level audiences. Ability to create impactful data visualisations that support insight communication. Our ideal candidate will possess: Strong attention to detail and a curiosity for uncovering hidden patterns in data. A highly analytical mindset, with a structured and hypothesis-driven approach to problem solving. The ability to operate in ambiguous environments with incomplete or imperfect data, applying reasoning to reach sound, defensible conclusions. The ability to connect analytical findings to real-world business impact and customer outcomes. Strong communication and collaboration skills, particularly when working with commercial and non-technical stakeholders. A proactive mindset with a willingness to experiment with new analytical approaches and tools, including AI. A self-driven approach to adopting new technologies and rapidly building proficiency.