About the job
At Signifyd, we empower merchants to confidently expand their businesses by fostering trusted relationships with their customers. Our cutting-edge technology, paired with a dedicated team committed to our clients' success, creates seamless shopping experiences, approving more legitimate orders, safeguarding revenue, and ensuring customer satisfaction.
Trusted by thousands of leading merchants across over 100 countries, we securely process billions of transactions annually. Our people are the core of our operations, propelling our mission forward with dedication, empathy, and creativity. Join us in our quest to enable fearless commerce by assisting online retailers in delivering exceptional customer experiences and combatting fraud. Discover our company values here!
Department: Risk Intelligence
The Risk Intelligence team at Signifyd is tasked with proactively identifying and continuously monitoring fraudulent activities to prevent immediate financial losses and protect the health of our portfolio. This team collaborates closely with Data Science to enhance machine learning (ML) model performance by providing ongoing feedback on model outputs and pinpointing areas for improvement using real-world fraud patterns and merchant feedback. We refine detection mechanisms to minimize friction for merchants and their customers while driving revenue. We instill trust through responsiveness and expertise, cultivating stronger merchant relationships. We demonstrate the value of fraud prevention solutions in driving revenue growth and mitigating losses.
The Role:
As a Risk Analyst, you will have the chance to join a team of seasoned fraud experts and deepen your understanding of fraud mitigation within the e-commerce sector. Your analytical mindset, technical skills, and relentless spirit will significantly enhance our team's ability to swiftly respond to threats, outsmart fraudsters, and elevate payment risk decision-making processes.
Your daily tasks will include:
- Analyzing large datasets to identify and extrapolate fraud trends and recommend effective, refined solutions.
- Monitoring performance dashboards to identify anomalies.
- Investigating high-risk alerts.
- Creating analytical reports that deliver actionable insights on fraud patterns.
- Proposing ideas for new Machine Learning features or rules, working closely with Data Science teams to enhance model performance.
- Staying updated on the latest fraud trends.

