ApplySarthiData Science Manager
Gocardless
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Preparing for this interview
Interviews for science roles keep coming back to Python, Machine learning, SQL, R. Practise those questions before you sit with Gocardless.
Questions you are likely to be asked
- Why do you want to join Gocardless?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Data Science Manager at Gocardless interview free →About us
GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday.
We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn ----- is the leading payments and financial services partner for business, rooted in Europe, with global reach.
The role
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.
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.
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.
What you’ll do
- Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development.
- Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions.
- Shape the strategic roadmap for the Payment Intelligence space, translating complex data challenges into actionable, high-impact goals.
- Drive cross-functional impact by working closely across disciplines to build end-to-end technical solutions, from concept to production.
- Influence Senior Leadership by acting as the bridge between technical complexity and business value, communicating ML strategy to senior stakeholders.
What excites you
- Driving cutting-edge advancements in Data, AI, and Machine Learning within the payments space with a multidisciplinary team.
- Mentoring a high-performing team and fostering a culture of technical excellence.
- Solving the complex, real-time challenges of fraud prevention and payment optimisation at scale.
- Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.
What excites us
- 2+ years managing Data Scientists within complex, high-stakes domains.
- 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.
- A decisive collaborator who can navigate technical trade-offs and translate complex ML concepts for cross-functional stakeholders and leadership.
- Familiarity with complex data environments and model architectures, such as deep learning (experience in Fintech, Fraud Prevention, or Payments is a big plus).
Base salary range: £99,200 - £148,800
Base salary ranges are based on role, job level, location, and market data. Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work.
(some of) The good stuff
- Wellbeing - stay healthy with dedicated support and medical cover
- Work away scheme - gives you the option to work away from your country of residence for up to 90 days in any 12 month period
- Adaptive Working - allows you to work flexibly, around your lifestyle
- Parental leave - to suit everyone embarking on life's great adventure
- Learning Budget - lead your own development with an annual learning budget
- Time off - generous holiday allowance, + 3 annual volunteer days, + 4 annual business-wide wellness days (‘GC Fridays’)
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
As of April 2025, we had 806 employees (GeeCees) globally, with 524 based in the UK, 163 based in Latvia and 119 across our other offices.
To ensure that we're representative of the world around us - and to be able to review relevant benchmarks - we ask GeeCees to voluntarily disclose diversity data. This year, the proportion of GeeCees providing data increased to 88% (up from 79% in 2024). With regards to diversity within GoCardless, we can see GeeCees identifying as:
Asian, Black, Mixed or Other — 25%
Neurodiverse — 9%
LGBTQIA+ — 9%
Disabled — 1%
Average age — 33
Female — 45%
Male — 55%
We’re rooting for you during your application and GoCardless aims to provide reasonable adjustments to make our recruitment process as remarkable and accessible as we can. Please speak to your Talent Partner if you need extra support.
If you want to learn more, you can read about our Employee Resource Groups and objectives here
Sustainability
We’re committed to reducing our impact on the environment, leaving a more sustainable world for future generations. Check out our sustainability action plan here.
Find out more about Life at GoCardless via Twitter, Instagram and LinkedIn.
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Listed on arbeitnow · posted 2026-10-10. ApplySarthi collects openings and links to application pages; the role is advertised by Gocardless, not by us.