Fraud Data Analyst - Merchant Facing
Checkout.com · Tel Aviv
About this role
Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech - and we’re just getting started. Job Description About the role As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Data Analyst to join our growing Fraud Analytics team. We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions. This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us. Key Responsibilities - Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns. - Partner with cross-functional teams, including software engineers, data scientists, and
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