Job Opportunities API

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We’re looking for a curious and analytical Fraud Detection Analyst to join our global Fraud & Investigations team. You’ll analyse data, spot patterns, and write detection rules that help stop fraud in its tracks — playing a vital role in protecting consumers, businesses, and the integrity of our platform. You’ll work on complex, often ambiguous challenges in the ever-evolving world of online trust. If you love solving problems, diving into data, and making a real difference - this is your chance. You’ll be joining a collaborative, inquisitive team that values transparency, fairness, and a good sense of humour. As part of the wider Trust & Transparency team, we’re driving change across the business—and working to make Trustpilot the universal symbol of trust online. What you'll be doing: Hunt for novel fraud on the platform, form hypotheses about how bad actors operate, then prove or disprove them in data that rarely offers a clean answer. Invent detection logic from scratch: design the features, criteria, and thresholds that separate fraudulent behaviour from the millions of legitimate reviews it hides among. Engineer that logic into production grade detection rules in SQL, carefully structured, logically sound, and built to keep working as fraudsters adapt. Own the false positive problem. Every rule you write can affect real people and businesses, so you'll obsess over precision as much as coverage, building in the exclusions and safeguards that protect legitimate users. Investigate escalated cases of platform misuse, and assist with media, legal, and customer inquiries. Partner with data scientists to sharpen our detection approaches, and work with engineering to improve the tools and data infrastructure that let your rules scale. Act as a resource for other teams by analysing reviewer and business behaviour, and communicate your findings and reasoning clearly to both technical and non-technical stakeholders. Work closely with and report to our Manager of Fraud Analytics. Who you are: You think like an adversary. When you see a system, you instinctively wonder how someone would game it, and you enjoy the cat-and-mouse of staying ahead of them. You're creative with data, not just fluent in it. You can look at a messy, ambiguous dataset and invent a new way to slice it that exposes something nobody had noticed. You build, not just report. You're comfortable writing SQL that goes beyond extraction and joins into genuinely complex, logically layered logic, the kind that becomes a standing detection rule, not a one off query. (We work in SQL, BigQuery, and Looker; deep SQL capability matters more than any specific tool.) You have strong instincts about the tradeoff between catching fraud and wrongly flagging innocent people, and you treat false positives as a serious cost, not an afterthought. You can hold a fuzzy, open ended problem in your head, break it into testable pieces, and stay with it. A lot of this work is ambiguous, and the answer isn't in a playbook. Experience in data analytics or a similar analytical field, whether through formal education (Science, Maths, Computer Science, or similar) or equivalent hands on experience. Prior fraud or abuse detection experience is welcome but not required, we care more about how you think than what domain you've worked in. What’s in it for you: A range of flexible working options to dedicate time to what matters to you Competitive compensation package + bonus 25 days holiday per year, increasing to 28 days after 2 years of employment  Two (paid) volunteering days a yea