Risk Intelligence Manager

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.

Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values here!

Job Title: Risk Intelligence Manager

Department: Risk Intelligence
The Risk Intelligence organization at Signifyd is responsible for proactively detecting and continuously monitoring fraud activities to mitigate immediate financial losses and protect portfolio health. This team partners closely with Data Science to improve machine learning (ML) model performance by providing continuous feedback on model outputs and identifying areas for enhancement using real-world fraud patterns and merchant feedback. We enhance detection mechanisms to reduce friction for merchants and their customers while driving revenue. We build trust through responsiveness and expertise, fostering stronger merchant relationships. We demonstrate the value of fraud prevention solutions in driving revenue growth and reducing losses.

About the role:

In this role, you will lead and develop a team of fraud analysts who investigate emerging threats, respond to fraud incidents, and translate behavioral insights into effective risk strategies. You will strengthen the people, tools, processes, and analytical standards that enable the team to succeed. This includes coaching analysts, improving investigative practices, establishing best practices, and helping team members develop the skills needed to solve increasingly complex risk problems.

You will partner closely with Risk leadership and teams across Data Science, Customer Success, Product, and Engineering. Together, you will turn investigative findings into scalable improvements that reduce fraud losses, support intelligent risk-taking, and improve customer experiences. Success in this role requires strong people leadership, analytical judgment, operational discipline, and the ability to communicate complex risk issues clearly to technical, business, and customer audiences.

At Signifyd, you will be part of a purpose-driven company dedicated to creating a dynamic and versatile work environment. Risk Intelligence is an integral part of our growing organization that values neighborly collaboration, passion, and inventiveness. 

Responsibilities: 

• Hire, coach, and performance-manage a team of fraud analysts, closing skill gaps and serving as the escalation resource for complex investigations and emerging attacks.
• Own and improve the standards, playbooks, and tools for incident response, case review, merchant onboarding, decision transparency, and rule design where historical data is limited.
• Turn investigative findings into clear recommendations for the teams responsible for business and customer outcomes, and represent Risk Intelligence in cross-functional initiatives.
• Partner with business-unit leaders, Data Science, Customer Success, Product, and Engineering to close capability gaps and turn fraud behaviors into durable signals, features, and model improvements.
• Support customer conversations as a fraud subject-matter expert, explaining risk decisions and sharing effective practices. Coach analysts to communicate risk insights clearly and build confidence presenting to customers.

Requirements:

• 3+ years of direct people management, including coaching and performance management, with a track record of building an effective team.
• 5+ years in ecommerce, payments, fraud prevention, or risk management, including fraud investigations and emerging-threat response.
• Advanced analytical judgment, including balancing fraud losses, customer experience, and intelligent risk-taking.
• Experience building operational standards, playbooks, and workflows, and the discipline to improve how a team works.
• Effective communication skills presenting to a variety of technical, business, and customer audiences
• Solid cross-functional experience partnering with data science, customer success, product, or engineering.

#LI-Remote

Benefits in our US offices:

• Discretionary Time Off Policy (Unlimited!)
• 401K Match
• Stock Options
• Annual Performance Bonus or Commissions
• Paid Parental Leave (12 weeks)
• On-Demand Therapy for all employees & their dependents
• Dedicated learning budget through Learnerbly
• Health Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Account (FSA)
• Short Term and Long Term Disability Insurance
• Life Insurance
• Company Social Events
• Signifyd Swag

Compensation: 

In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.

Base Salary Ranges by Pay Zone:

• Tier 1 (NYC/SF Bay Area/Seattle): $120,000 – $140,000 annually
• Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego): $110,000 – $130,000 annually
• Tier 3 (US - All Other): $100,000– $120,000 annually

Equity: This role is eligible for a stock option grant of 1500 stock options, based on the position level and internal compensation guidelines. 

Bonus: This role is eligible for an annual performance bonus of up to 10% of base salary.

We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

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