Data Science Manager

GoCardless
Riga, Latvia€64k – €96kPosted 21 February 2026

Job Description

<div class="content-intro"><h3><strong>About Us at GoCardless</strong></h3> <p>GoCardless is a <strong>global bank payment</strong> company. Over <strong>100,000 businesses</strong>, from start-ups to household names, use GoCardless to collect and send payments through direct debit, real-time payments and open banking. </p> <p>GoCardless processes <strong>US$130bn+</strong> of payments annually, across <strong>30+ countries</strong>; helping customers collect and send both <strong>recurring</strong> and <strong>one-off payments</strong>, without the chasing, stress or expensive fees. We use AI-powered solutions to improve payment success and reduce fraud. And, with open banking connectivity to over <strong>2,500 banks</strong>, we help our customers make faster, more informed decisions.</p> <p>We are headquartered in the<strong> UK</strong> with offices in <strong>London</strong> and <strong>Leeds</strong>, and additional locations in <strong>Australia, France, Ireland, Latvia, Portugal</strong> and the <strong>United States.</strong></p> <p>At GoCardless, we're all about <strong>supporting you</strong>! We’re committed to making our hiring process <strong>inclusive</strong> and <strong>accessible</strong>. If you need extra support or adjustments, reach out to your <strong>Talent Partner</strong> — we’re here to help! </p> <p>And remember: we don’t expect you to meet every single requirement. If you’re excited by this role, <strong>we encourage you to apply!</strong></p></div><h3>The role</h3> <p>Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention.</p> <p>As a Data Science Manager within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network.</p> <p>At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale.</p> <h3><strong>What you’ll do</strong></h3> <ul> <li>Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development.</li> <li>Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions.</li> <li>Shape the strategic roadmap for the Payment Intelligence space, translating complex data challenges into actionable, high-impact goals.</li> <li>Drive cross-functional impact by working closely across disciplines to build end-to-end technical solutions, from concept to production.</li> <li>Influence Senior Leadership by acting as the bridge between technical complexity and business value, communicating ML strategy to senior stakeholders.</li> </ul> <h3><strong>What excites you</strong></h3> <ul> <li>Driving cutting-edge advancements in Data, AI, and Machine Learning within the payments space with a multidisciplinary team.</li> <li>Mentoring a high-performing team and fostering a culture of technical excellence.</li> <li>Solving the complex, real-time challenges of fraud prevention and payment optimisation at scale.</li> <li>Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.</li> </ul> <h3><strong>What excites us</strong></h3> <ul> <li>2+ years managing Data Scientists within complex, high-stakes domains.</li> <li>A hands-on leader comfortable diving into the codebase. You bring strong expertise in Python and SQL to oversee the full lifecycle of a model, from initial prototype to robust production deployment.</li> <li>A decisive collaborator who can n ... (truncated, view full listing at source)