At a Glance
- Tasks: Develop and deploy predictive models to prevent fraud and enhance payment security.
- Company: Join GoCardless, a leading global bank payment company with a mission to simplify payments.
- Benefits: Enjoy flexible hybrid working, medical cover, equity options, and generous time off.
- Why this job: Make a real impact in fintech by innovating fraud prevention solutions with cutting-edge technology.
- Qualifications: Degree in STEM or equivalent experience; strong skills in deploying predictive models.
- Other info: Be part of a diverse team committed to sustainability and inclusivity.
The predicted salary is between 36000 - 60000 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.
At GoCardless, we’re all about supporting you! We’re committed to making our hiring process inclusive and accessible. If you need extra support or adjustments, reach out to your Talent Partner — we’re here to help! And remember: we don’t expect you to meet every single requirement. If you’re excited by this role, we encourage you to apply!
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.
Life at GoCardless:
We’re an organisation defined by our values; We start with why before we begin any project, to ensure it’s aligned with our mission. We make it happen, working with urgency and taking personal accountability for getting things done. We act with integrity, always. We care deeply about what we do and we know it’s essential that we be humble whilst we do it. Our Values form part of the GoCardless DNA, and are used to not only help us nurture and develop our culture, but to deliver impactful work that will help us to achieve our vision.
Diversity & Inclusion:
- 45% identify as women
- 23% identify as Black, Asian, Mixed, or Other
- 10% identify as LGBTQIA+
- 9% identify as neurodiverse
- 2% identify as disabled
If you want to learn more, you can read about our Employee Resource Groups and objectives here as well as our latest D&I Report.
Sustainability at GoCardless:
We’re committed to reducing our environmental impact and leaving a sustainable world for future generations. As co‑founders of the Tech Zero coalition, we’re working towards a climate‑positive future.
Data Scientist Lisbon, Portugal employer: GoCardless
Contact Detail:
GoCardless Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist Lisbon, Portugal
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at GoCardless. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or some projects that highlight your data science prowess, make sure to share them. Real-world examples speak volumes!
✨Tip Number 3
Prepare for the interview by diving deep into GoCardless's mission and values. Tailor your answers to show how you align with their goals, especially around fraud prevention and fintech innovation.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Data Scientist Lisbon, Portugal
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role at GoCardless. Highlight your experience with predictive models and any relevant work in fintech or fraud prevention. We want to see how your skills align with what we do!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for fraud prevention and how you can contribute to our mission. Be sure to mention specific projects or experiences that demonstrate your expertise in ML solutions.
Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially in coding and model deployment. We love seeing candidates who can communicate complex ML concepts clearly, so include examples of how you've done this in the past.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we’re here to support you throughout the process!
How to prepare for a job interview at GoCardless
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and fraud prevention strategies. 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 Your Collaboration Skills
Since this role involves working closely with engineers and analysts, be prepared to share examples of how you've successfully collaborated in the past. Highlight any cross-functional projects where you turned complex data into actionable insights, as this will demonstrate your ability to work well within a team.
✨Ask Smart Questions
Prepare thoughtful questions about GoCardless's approach to fraud prevention and their use of AI. This shows your genuine interest in the company and the role. It’s also a great way to gauge if their values align with yours, especially around innovation and integrity.
✨Be Yourself
GoCardless values authenticity, so don’t be afraid to let your personality shine through. Share what excites you about the role and how you see yourself contributing to their mission. Remember, they’re looking for someone who fits into their culture, so being genuine is key!