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).

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 Senior Data Scientist 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

• Lead 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 and engineering 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.
• Proactively research and integrate 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.
• An opportunity to introduce and scale advanced architectures to solve high-stakes fraud and payment challenges.
• Moving beyond execution to help define the technical roadmap for Payer Fraud Prevention, ensuring we leverage the best tools for the job.
• 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 bring hands-on experience with sophisticated architectures, such as deep learning, graph-based, or sequence-based models (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 comfortable owning the full lifecycle, from deep-dive analysis and feature engineering to prototyping, validation, and live A/B testing.
• You lead by example, writing clean, high-quality code and raising the team’s technical bar through knowledge sharing and code best practices.

The role

Fraud prevention is an ever-evolving puzzle, making it one of the most rewarding and impactful areas in fintech. At GoCardless, our Fraud Prevention team develops the intelligent systems that protect our platform, our merchants, and their customers.

As a Senior Data Scientist, you will guide the design and delivery of models that operate in real time across our global payment network. You’ll work at the intersection of machine learning, graph-based detection, and behavioural modelling to stay ahead of changing patterns turning research into production systems that make a tangible difference in the fight against financial crime.

You’ll collaborate closely with Engineers, Fraud Analysts, and Product Managers to help shape the technical roadmap as we expand into new markets. Our stack is centred around Google Cloud Platform and Vertex AI, using Python, SQL, and BigQuery to build and support high-performance models at scale.

What you'll do

• Contribute to the full model lifecycle, from initial discovery and feature engineering through to production, experimentation, and continuous monitoring.
• Design and refine real-time ML systems that reduce false positives and ensure a smooth, secure experience for legitimate customers.
• Foster a responsive feedback loop, adapting models as patterns evolve to ensure our defences remain robust and effective.
• Help shape the technical direction of fraud prevention ML at GoCardless, exploring new approaches as we grow globally.
• Support the team’s growth through technical mentorship, knowledge sharing, and a commitment to high-quality code.

What excites you

• Solving complex, dynamic problems: Developing systems that can adapt and respond to changing environments.
• End-to-end ownership: Seeing a project through from a conceptual business need to a live, impactful solution.
• Strategic influence: Contributing to the ML roadmap and helping determine what we build next, rather than just how we build it.
• Holistic Data Science: Engaging in deep-dive analysis, prototyping, and live experimentation.
• Modern Infrastructure: Building production-grade models on GCP and Vertex AI, with the flexibility to explore advanced architectures.

What excites us

• You hold a degree (or PhD) in a STEM discipline, or bring equivalent depth through commercial experience.

• You have hands-on experience with modelling approaches such as deep learning, graph-based methods, or sequence models. While fintech experience is great, we value transferable skills from fields like cybersecurity or risk modelling.
• You have a track record of deploying models in production that create measurable value.
• You can translate complex ML concepts into clear, practical solutions for stakeholders across the business.
• You enjoy writing clean code and helping the team thrive through thoughtful reviews and shared learning.

Base salary range: €64,000 - €96,000

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.

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 Senior Data Scientist 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

• Lead 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 and engineering 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.
• Proactively research and integrate 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.
• An opportunity to introduce and scale advanced architectures to solve high-stakes fraud and payment challenges.
• Moving beyond execution to help define the technical roadmap for Payer Fraud Prevention, ensuring we leverage the best tools for the job.
• 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 bring hands-on experience with sophisticated architectures, such as deep learning, graph-based, or sequence-based models (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 comfortable owning the full lifecycle, from deep-dive analysis and feature engineering to prototyping, validation, and live A/B testing.
• You lead by example, writing clean, high-quality code and raising the team’s technical bar through knowledge sharing and code best practices.

Base salary range: €64,000 - €96,000

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.

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 Senior Data Scientist 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

• Lead 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 and engineering 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.
• Proactively research and integrate 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.
• An opportunity to introduce and scale advanced architectures to solve high-stakes fraud and payment challenges.
• Moving beyond execution to help define the technical roadmap for Payer Fraud Prevention, ensuring we leverage the best tools for the job.
• 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 bring hands-on experience with sophisticated architectures, such as deep learning, graph-based, or sequence-based models (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 comfortable owning the full lifecycle, from deep-dive analysis and feature engineering to prototyping, validation, and live A/B testing.
• You lead by example, writing clean, high-quality code and raising the team’s technical bar through knowledge sharing and code best practices.

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.

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: €64,000 - €96,000

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.

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.