Staff Data Scientist

Signifyd helps businesses of all sizes minimize their fraud exposure and grow their sales. Signifyd improves the e-commerce shopping experience for everyone by reducing the number of false positive declines of good buyers and by making fraud less profitable for criminals.

The Data Science organization at Signifyd is responsible for building, maintaining, and monitoring production ML models and risk management tools that are the core of Signifyd's product. The Staff Data Scientist will be part of the Core ML team within the Data Science organization. The team owns the core fraud detection model that decides the majority of the traffic, as well as our model training and evaluation infrastructure. We work closely with the ML and Data Platform teams. The team contributes to: novel modeling methods, advanced feature engineering, and robust statistical practices for offline and online evaluation. 

Our culture: we value tenacity, curiosity, and a hunger for learning. Our adversaries are highly motivated fraudsters who are looking to exploit any gap that we may leave uncovered. We seek equally motivated – if not more motivated – individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward. 

We empower team members to influence our direction and actively enhance the e-commerce shopping experience. 

Signifyd is looking to add a few Staff Data Scientists to our team. As a Staff Data Scientist, you’ll play a pivotal role in shaping the future of our machine learning capabilities. You won’t just build models—you’ll influence strategy, mentor teams, and drive measurable improvements in our fraud detection systems. You’ll be responsible for solving critical challenges in model performance measurement, accelerating experimentation, and pioneering new ML technologies to stay ahead of evolving fraud tactics.

• Expand ML Capabilities – Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
• Drive Experimentation at Scale – Develop and implement robust experimentation frameworks to increase velocity while maintaining scientific rigor, enabling rapid iteration and deployment of fraud detection models.
• Architect & Optimize ML Pipelines – Design and build scalable, end-to-end ML pipelines that support both offline and online measurement of model performance, ensuring our models deliver real-world impact.
• Build Influence Across Teams – Collaborate closely with engineering, product, and risk teams to align ML architecture and experimentation with business goals, driving measurable outcomes.
• Lead & Mentor – Lead solving the technical concerns for the entire organization and elevate the technical bar by mentoring data scientists and engineers, sharing best practices, and fostering a culture of innovation and excellence in ML practices.

• A degree in computer science or a comparable analytical field
• 7+ years of post-undergrad work experience with production-grade ML 
• Deep ML expertise with a solid foundation in machine learning, experimentation, and model evaluation techniques.
• Proven experience leading technical initiatives and influencing decision-making across teams. 
• Strong communication skills– You are great at breaking down complex ML and DS topics to non-technical audiences. You are also great at using visualization to communicate analytical results. 
• Strong product & business mindset with a passion for applying data science to solve real-world problems with measurable outcomes.
• Proficiency in Python, SQL, and key ML libraries. 

Bonus points if you have:

• Previous work in fraud, payments, or e-commerce
• Passion for writing well-tested production-grade code
• A Master's Degree or PhD

• Make an Impact – Your work will directly shape the future of fraud prevention, protecting billions of payments.
• Lead & Grow – Drive high-visibility initiatives and develop leadership skills in a fast-paced, high-growth environment.
• Innovate at Scale – Work with cutting-edge ML technologies and experiment freely to push the boundaries of what’s possible.

Collaborative Culture – Join a team that values curiosity, ownership, and continuous learning.

#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

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.