Threat Analyst

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, BioCatch counts over 25 of the top 100 global banks as customers who use BioCatch solutions to fight fraud, drive digital transformation, and accelerate business growth. 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.

Come and work with intensely curious people who are dedicated to innovation, growth, and protecting customers against cybercrime and fraud

We are looking for an exceptional customer-facing Threat Analyst to help our prospects and customers optimize their value within BioCatch solutions. The BioCatch Threat Analyst is a consultancy role that involves a combination of skills. You will be comfortable completing advanced analytics, advising customers on fraud detection/prevention and strategy with your domain knowledge expertise and communicating with customers from C-level to operational fraud investigators. This role is unique in the industry and to be successful, you must be a motivated self-starter who can ramp-up quickly and work autonomously. With a support network of Threat Analysts distributed globally, you will become a key individual in the global fight against digital fraud.

It can be difficult to distill this role down to a regular day-to-day, because every day is different, however some key responsibilities include:

• Build and maintain strong partnerships with AML and financial crime teams within the BioCatch customer base to ensure they derive maximum value from BioCatch solutions.
• Provide subject matter expertise (SME) in AML and financial crime to help customers achieve their strategic objectives in compliance, fraud prevention, and risk mitigation.
• Collaborate with customers and BioCatch Data Science to improve detection of money laundering patterns and financial crime, while ensuring minimal disruption for legitimate users.
• Apply a data-driven approach to demonstrate the effectiveness of BioCatch solutions against customer success criteria in proof of value and pilot engagements.
• Educate potential and existing customers on how BioCatch and Behavioral Biometrics can address key AML and financial crime challenges and use cases.
• Work closely with customers to design and deploy detection strategies for emerging threats such as mule account activity, layering schemes, and complex financial crime typologies.
• Guide customers toward best practices in AML detection, compliance, and fraud risk management.
• Act as the voice of the customer to internal BioCatch teams, influencing product strategy and development in line with AML and financial crime priorities.
• Support BioCatch Data Science in researching new and emerging threats across our main use cases including Account Takeover, Account Opening, Remote Access Scams, Social Engineering Scams and Mule detection
• Deliver actionable reporting and insights on AML and financial crime detection performance.
• Share industry learnings, case studies, and insights with Sales Enablement to strengthen BioCatch's position as a thought leader in financial crime prevention.
• Provide AML and financial crime SME support to BioCatch Sales teams to accelerate new customer acquisition and deepen customer engagement.

• Bachelor's or graduate degree in Computer Science, Mathematics, Statistics, Economics, or a related field.
• Experience working within financial institutions' Financial Crime, AML, or Compliance functions, with exposure to transaction monitoring, sanctions screening, or fraud/AML investigation tools.
• Proven ability to collaborate effectively across cross-functional teams, including Compliance, Risk, Data Science, and Operations.
• Strong analytical skills with hands-on experience using SQL at an intermediate/advanced level to analyze large transaction datasets and identify suspicious activity.
• Experience with Python and/or R for data analysis, automation, or model development (advantageous).
• Solid understanding of statistical modeling, anomaly detection, or machine learning techniques applied to financial crime and AML risk detection.
• Certified Anti-Money Laundering Specialist (ACAMS) certification highly desirable and considered an advantage for candidates applying for this role.
• Strong presentation and storytelling skills with a track record of delivering insights to compliance officers, regulators, and senior stakeholders.
• Demonstrated ability to build strong business partnerships and customer relationships in financial crime or compliance contexts.
• Excellent communication skills and a collaborative mindset to drive AML and financial crime initiatives forward.

Location: Sydney or Melbourne