Data Science Manager – (Fake Review Detection)

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 a leading online reviews platform, free and open to all. Our mission is to be a universal symbol of trust. We are well on our way - but there’s still an exciting journey ahead of us. Do you want to join us? A core value proposition of Trustpilot is Trust. We work hard to ensure that our platform has real content from real people with real experiences. That means eliminating fraudulent reviews and sanctioning suspect behavior to keep our platform authentic. Our Trust Technology team aims to be an established name in the use of advanced technology to safeguard the integrity of online reviews. The Trust teams are composed of both Engineering and Data Science functions, where both are integral to achieving our goals. We are looking for a skilled Data Science Manager to join the Trust team in our mission. You will lead two teams of passionate and dedicated professionals, including Data Scientists who research Trust-specific problems and design ML solutions for them, and Engineers who build and maintain scalable infrastructure to turn detections into outcomes. You and your team will work within a focus area to develop, deploy, and maintain innovative technology at scale, alongside a cross-functional team of product managers, ML engineers, and designers. You will have the opportunity to collaborate widely across the business including with those in our Legal, Platform Engineering, and Data Science teams within Consumer, B2B, and Commercial. To thrive in this role, you bring a background in building and scaling complex systems with machine learning at their core. You are a seasoned Data Scientist who enjoys remaining hands-on across the end-to-end lifecycle—from initial concept to production delivery. Bridging data science and engineering comes naturally to you, supported by an adaptable, curious mindset. While not required, prior exposure to fraud detection or online platform integrity is a great plus. What you’ll be doing: • Lead and empower a team of Data Scientists and Engineers within the Trust context, focused on detection of fake reviews. • Own the delivery of key initiatives and balance delivery with ambitious research goals and sustainable engineering practices. • Foster a culture of technical excellence and actively support the development of your team members. • Define, prioritise, and support the implementation of deliverables that achieve our Trust OKRs. • Facilitate scoping, estimation, and planning of work in collaboration with the cross-functional teams. • Build strong relationships with our Trust stakeholders and other teams. • Communicate issues, risks, and dependencies with stakeholders. • Collaborate with Trust Tech leadership to engage, develop and retain talent. • Build a positive and safe working environment based on transparency, accountability, and trust. Who you are: • Experienced in a complex technical domain (such as fraud detection, healthcare ML, computer vision, autonomous systems, or large-scale LLM deployment), with a natural curiosity to immerse yourself in our field. • Experience with delivering scalable systems with multiple connected services, and designing solutions involving ML/AI components. Experience with graphs and graph-based ML is a significant advantage. Other relevant experience includes: high-volume live inference, ML training / deep learning on cloud infrastructure on large datasets, training with mixed-quality labels for production use cases, opti