Fraud Analyst - London

London | Full - time | Hybrid | Shoreditch/Liverpool Street

Whether it's visiting the people closest to us, starting an exciting adventure, or a career defining business trip, travel is essential. Yet we've all experienced the aches and pains of getting to our destination.

More than 4 billion airline passengers rely on technology that hasn't kept up with modern expectations. That's why we're rebuilding the infrastructure that underpins the travel industry simplifying systems and building tools that will make the future of travel effortless. Central to this mission is ensuring seamless, secure and reliable payment experiences, which are crucial for every transaction and a cornerstone of trust in our platform.

We were part of Y Combinator S18's cohort and backed by Benchmark, Blossom, Index Ventures, and Kima Ventures a fantastic set of investors that has helped build some of the world's largest companies.

Our London team is growing, and we're looking for an experienced Fraud Analyst join us on our journey.

We're looking for a curious and analytical Fraud Analyst to join our team. You'll analyse data, spot patterns, and write detection rules that help stop fraud in its tracks playing a vital role in protecting travellers businesses, and the integrity of our platform.

You'll work on complex, often ambiguous challenges in the ever ,evolving world of travel payments and bookings. If you love solving problems, diving into data, and making a real difference this is your chance.

• Identify fraud trends and develop a deep understanding of fraudulent behaviour on our platform through SQL, Google BigQuery, and Google Looker

• Formulate rules based on your analysis to mitigate fraudulent behaviour across our platform

• Carry out investigations of escalated cases related to potential misuse of our platform and assist with legal and customer enquiries

• Partner with our data science and engineering teams to advance our technological approaches to identifying fraudulent activity

• Work closely with engineering to enhance internal tools and databases that enable us to combat fraud and scale effectively

• Act as a key resource for other departments by providing analysis of customer and booking behaviour on the platform

• Present and communicate the results of analyses and investigations to stakeholders across the company

• You have experience in data analytics or a similar analytical role (through formal education or practical experience)

• You're comfortable working with and interpreting large datasets

• You have a knack for answering difficult questions using data and translating complex findings into clear, actionable reports

• You're proficient in writing queries and preparing reports using SQL or similar

• You're motivated by self ,learning and growing your skills when faced with new challenges

• You can manage multiple priorities effectively with a proactive, forward ,thinking mindset

Bonus: Prior knowledge of formulating rules to combat fraudulent behaviour or experience in travel/payments

•💰 Competitive salary + equity (you'll own part of Duffel)

• 🏝️ Work from anywhere policy

• 🛩️ Duffel travel allowance (use what we build)

• 🍼 Generous parental leave

• 🧘‍♂️ Sabbatical programme

• 🪩 Office in Shoreditch + regular team socials

As we scale to millions of bookings, fraud prevention becomes critical. You'll build the systems and rules that protect our platform from day one of this function, defining how we approach trust and security as we grow.

We're an equal opportunities employer. We believe that the key to our success is employing a diverse team, which is why recruitment decisions are only based on your experience and skills. We welcome applications from everyone  ,regardless of age, sex, disability, sexual orientation, race, religion, or belief.

Note to recruitment agencies: Duffel does not accept speculative CVs from external parties. Any unsolicited CVs sent to us will be treated as property of Duffel, and any attached terms and conditions associated with these CVs will be null and void.