About Us

Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Wayfair, Acer, Gucci, Lorna Jane, GoPro, and many more.

We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day.

About the Role

The Data Science department plays a pivotal role in our company, generating value for Riskified by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to extract maximum value from data of all shapes and sizes, including classification models, NLP, anomaly detection, graph theory, deep learning, and more.

Our models and algorithms are integrated into Riskified's product's critical path, helping to make thousands of decisions per second in real-time. All the capabilities we develop must meet production-grade requirements in both analytical and engineering standards.

As the Fraud Researcher, You will get to work with smart, experienced analysts, data scientists, and engineers who build multi-layered products while gaining a deep understanding of the fraud and payments industry. You will be responsible for researching and identifying emerging fraud trends and collaborating closely with Riskified’s Product Managers across cross-functional teams to transform these findings into meaningful fraud-prevention / payment solutions that align with company goals.

What You'll Be Doing

• Be an expert in payment fraud and abuse, one who deeply understands e-commerce customers' and fraudsters' behavior through real-time systems. You must bring great ability and experience in understanding fraud patterns across clusters of orders/networks and in working with complex architecture that supports order-level and identity-level design.
• Drive deep-level analysis of fraud attacks to allow productization of best-in-class solutions. As the Fraud Researcher, you will need to plan, design, analyze, and present large fraud attacks and patterns, explain the root causes, and suggest efficient solutions to mitigate such in the future.
• Work with GTM teams to share and explain examples of fraud and abuse trends we have identified.
• Understand the company objectives and proactively work with the different teams to develop strategies to achieve those goals.
• Collaborate with a team of industry-leading analysts, data scientists, and software engineers to develop the next generation of RSKD’s AI technology. You are expected to ideate new features and product solutions and bring them all the way to production.
• Leverage advanced analytical tools to analyze millions of transactions and identify emerging fraud trends that can be translated into meaningful insights and potential product developments.
• Build new and advanced investigation methods and procedures.
• Take E2E ownership of leading high-scale projects that include tight collaboration with global teams and presenting findings to stakeholders.

Qualifications

• Bachelor’s degree in exact sciences such as Statistics, Economics, Mathematics, or similar
• 4+ years of experience in fraud investigation and quantitative analysis in a similar company /role - A Must
• Vast experience in SQL and Python code-writing experience
• Has a keen eye for small details as well as a broad perspective to see the bigger picture
• Project management capabilities - you should be able to lead a domain independently, get buy-in from stakeholders across the company, maintain an organized knowledge base of your tasks, lead quarterly projects
• A fast mind, with strong attention to detail and an urge to understand everything you lay eyes on, especially the motivations behind the actions of individuals and institutions
• An algorithmic thinker with strong statistical and probabilistic intuition and a grasp of complex problems/solutions
• Excellent verbal & written communication skills (including strong English). Clearly convey and convince people of your view on complex issues

Life at Riskified

We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.

Our Tel-Aviv team is currently working in a hybrid of remote and in-office work. We have recently moved to our new space in Tel Aviv - check it out here!

Some of our Tel Aviv Benefits & Perks:

• Equity for all employees, Keren Hishtalmut, pension
• Private medical insurance, extra time off for parents and caregivers
• Commuter and parking benefits
• Team events, fully-stocked kitchen,lunch stipend, happy hours, yoga, pilates, functional training, basketball, soccer
• Wide-ranging opportunities to volunteer and make an impact
• Commitment to your professional development with global onboarding, skills-based courses, full access to Udemy, lunch & learns
• Awesome Riskified gifts and swag!

In the News

Geektime: Riskified Goes Public

Walla!: Happy Hour at the Riskified Offices

Geektime Insider: A look at Riskified Tel Aviv

Globes: Riskified to contribute the highest amount up to date to Tmura

Globes: Riskified is among Israel’s fastest growing companies

TechCrunch: Riskified Prevents Fraud on Your Favorite E-commerce Site

Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.