Threat Analyst

In this role, you will act as both a fraud analytics expert and a trusted advisor to financial institutions, helping them maximize the effectiveness of behavioral biometrics solutions while strengthening their fraud prevention strategies. You will combine hands-on data analysis with customer engagement and cross-functional collaboration to address real-world cyber threats.

• Serve as a subject matter expert supporting customers in optimizing fraud detection and prevention strategies using behavioral analytics tools.
• Build and maintain strong relationships with fraud operations teams, investigators, and executive stakeholders across financial institutions.
• Conduct advanced data analysis to evaluate fraud trends, detection performance, and system effectiveness using quantitative methods.
• Collaborate with internal data science and engineering teams to improve detection models and develop responses to emerging threats.
• Design, deploy, and fine-tune fraud detection rules to mitigate active fraud attacks and reduce customer friction.
• Provide data-driven reporting, insights, and performance evaluations for pilot programs and proof-of-value initiatives.
• Act as the voice of the customer by sharing insights and field intelligence to influence product strategy and roadmap decisions.
• Support sales and customer success teams by delivering technical expertise during pre-sales and onboarding processes.
• Research and monitor evolving fraud typologies, including account takeover, scams, and identity manipulation techniques.

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Requirements

The ideal candidate has strong analytical expertise combined with hands-on experience in fraud detection, data science, or threat analysis within financial services or security-focused environments. You are confident working with data, presenting insights to diverse audiences, and collaborating across technical and business teams.

• 3+ years of experience in threat analysis, fraud analytics, data analysis, or a related field within financial services or cybersecurity.
• Bachelor’s or graduate degree in Computer Science, Mathematics, Statistics, or a related quantitative discipline.
• Strong experience working with financial institutions’ fraud operations, monitoring systems, or investigative teams.
• Proficiency in SQL at an intermediate to advanced level for data extraction and analysis.
• Experience with Python and/or R is highly desirable for statistical and analytical modeling.
• Solid understanding of statistical modeling techniques and data-driven decision-making.
• Excellent communication and presentation skills, with experience engaging both technical teams and senior stakeholders.
• Strong business acumen with the ability to build trusted customer relationships and act in a consultative capacity.
• Self-starter mindset with the ability to work independently in a fast-paced, remote environment.
• Nice to have: experience with behavioral biometrics, machine learning applications, or large-scale fraud detection systems.

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Benefits

• Competitive salary range: $140,000 – $170,000 per year
• Flexible remote-first work arrangement across the United States
• Flexible paid time off policy
• Paid sick leave, maternity/paternity leave, and additional family-related leave options
• 401(k) retirement plan with up to 4% company match
• Comprehensive healthcare coverage tailored to employee needs
• Life insurance coverage
• Wellness programs, employee assistance program (EAP), and health advocacy services
• Monthly reimbursements for home internet and mobile phone expenses
• Opportunities for travel across North America for client engagement and workshops
• Strong focus on professional development and cross-functional learning

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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