At a Glance
- Tasks: Develop and deploy predictive models to prevent fraud and enhance payment security.
- Company: GoCardless, a leading global bank payment company with a focus on innovation.
- Benefits: Competitive salary, equity options, hybrid working, and generous leave policies.
- Why this job: Join a dynamic team shaping the future of fraud prevention in fintech.
- Qualifications: Degree in STEM or equivalent experience; expertise in deploying predictive models.
- Other info: Inclusive hiring process with support for all applicants.
The predicted salary is between 43200 - 72000 ÂŁ per year.
GoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect and send payments through direct debit, real-time payments and open banking. GoCardless processes US$130bn+ of payments annually, across 30+ countries; helping customers collect and send both recurring and one-off payments, 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 2,500 banks, we help our customers make faster, more informed decisions.
This role will be working within the Fraud Prevention team in our Merchant Operations Group. The Fraud Prevention team plays a critical role in protecting the integrity of the GoCardless platform by building systems that prevent and detect merchant fraud before it impacts our business or our customers. The Fraud Prevention Data Scientist will work closely with Engineers and Fraud Analysts to develop and deploy predictive models that strengthen our fraud defenses. You’ll focus on the end-to-end delivery of ML solutions – from feature engineering and prototyping to production‑grade deployment – to reduce false positives and automate controls without introducing unnecessary friction. You’ll also collaborate with cross‑functional stakeholders to ensure our ML products scale on our GCP stack, driving fintech innovation while supporting a seamless customer experience.
What you’ll do:
- Contribute to the end‑to‑end delivery of models at scale, from initial discovery and feature engineering to production, A/B testing and continuous monitoring.
- Collaborate with product, engineering and data science peers to turn complex data into real‑time, mission‑critical fraud prevention solutions.
- Raise the team’s collective bar through hands‑on technical leadership and knowledge sharing.
- Help bring to live the latest developments in ML and payer fraud prevention to drive innovation at GoCardless.
What excites you:
- Being a self‑starter who thrives on taking a vague business problem and owning the journey from the first prototype to a live, measurable solution.
- Contributing to the future of fraud prevention, by shaping up the data and ML products all the way from the initial insights to the market‑ready solutions.
- Working with a range of stakeholders to discover and design ML solutions, adapting them to the markets as we grow.
- Building production‑grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.
What excites us:
- You hold a degree (or PhD) in a STEM discipline or an equivalent commercial experience.
- You have a track record of deploying predictive models and data products in production with quantifiable impact (experience in Fintech, Fraud Prevention, or Payments is a big plus).
- You can translate complex ML concepts into practical product solutions and communicate these ideas clearly to non‑technical peers.
- You are experienced with writing and maintaining code to a production‑level standard, supporting the team with code reviews.
- You are comfortable contributing across the full model lifecycle, from deep‑dive analysis and feature engineering to prototyping, validation, and live A/B testing.
The Good Stuff!
- Wellbeing: Dedicated support and medical cover to keep you healthy.
- Work Away Scheme: Work from anywhere for up to 90 days in any 12‑month period.
- Hybrid Working: Our hybrid model offers flexibility, with in‑office days determined by your team.
- Equity: All permanently employed GeeCees get equity to share in our success.
- Parental leave: Tailored leave to support your life's great adventure.
- Time off: Annual holiday leave based on your location, supplemented by 3 volunteer days and 4 wellness days.
Senior Data Scientist, Fraud Prevention London, UK employer: GoCardless
Contact Detail:
GoCardless Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist, Fraud Prevention London, UK
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at GoCardless. A friendly chat can open doors and give you insider info that could make your application stand out.
✨Tip Number 2
Prepare for the interview by brushing up on your ML concepts and fraud prevention strategies. Be ready to discuss how you've tackled similar challenges in the past – real examples will impress!
✨Tip Number 3
Show your passion for fintech and fraud prevention! Share your thoughts on recent trends or innovations in the field during interviews. It shows you're not just looking for a job, but genuinely interested in making an impact.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re keen on joining the GoCardless team!
We think you need these skills to ace Senior Data Scientist, Fraud Prevention London, UK
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for the role shine through! We want to see how excited you are about fraud prevention and using data science to make a real impact at GoCardless.
Tailor Your CV: Make sure to customise your CV to highlight relevant experience in deploying predictive models and working with ML solutions. We love seeing how your background aligns with our mission to combat fraud!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on how your skills can contribute to our Fraud Prevention team.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and get the ball rolling on your journey with GoCardless.
How to prepare for a job interview at GoCardless
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning concepts and fraud prevention techniques. Be ready to discuss your past experiences with deploying predictive models and how they made an impact. This will show that you’re not just familiar with the theory, but you can also apply it in real-world scenarios.
✨Showcase Collaboration Skills
Since this role involves working closely with engineers and analysts, be prepared to share examples of how you've successfully collaborated with cross-functional teams in the past. Highlight any projects where you turned complex data into actionable insights, as this will demonstrate your ability to communicate effectively with both technical and non-technical peers.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Brush up on your coding skills and be ready to discuss your approach to feature engineering, model validation, and A/B testing. Practising coding challenges or discussing your thought process on past projects can help you feel more confident.
✨Be a Problem Solver
GoCardless is looking for self-starters who can take vague business problems and turn them into measurable solutions. Think of specific examples where you identified a problem, developed a solution, and implemented it successfully. This will showcase your initiative and problem-solving skills, which are crucial for this role.