Data at GoCardless 

You’ll sit in our Data & Business Systems group and will work with technical and non-technical people across the whole company. You’ll collaborate closely with our team of talented Analysts, Data Scientists, ML/AI Engineers and System Admins, designing and delivering first-class analytics to the business.

We’re a large team with an extensive remit and expect every member to work with initiative and be driven, holding each other accountable and to a high standard. Joining our team, you’ll work in a team that strives to be the best they can be. You’ll work on complex projects across GC’s data & business systems stack. 

You will enjoy being an analyst at GoCardless if:

• You’re looking to champion a great data culture within GC and in the wider data community. 
• You enjoy collaborating and learning from people from various backgrounds and experiences. 
• You want to feel proud of the work you’re doing and its impact on real customers.

Our technologies: We endeavour to build simple, reliable systems and we believe in using the best technologies for each task. Technologies we use across GoCardless include: Looker, Python, Looker, Google Cloud Platform, dbt, Airflow, Vertrex and Jupyter amongst others.

You’re not expected to have expertise in all these technologies. Members of our team have picked up the tools once they’ve started working with the team. 

The Role

At GoCardless we use marketing throughout the customer lifecycle to acquire new customers and drive revenue growth through our existing merchant base. As part of this role, you will be working closely across all marketing teams - paid, organic, lifecycle - to understand how their marketing efforts are helping to grow our merchant base and accelerate revenue. Your insights will be turned into actions as your expertise helps drive the future of GoCardless.

What excites you 

• Collaborate with Growth Marketing measuring how our Paid and Organic marketing strategies drive acquisition, engagement and revenue growth
• Partner with marketing stakeholders to define and monitor marketing KPIs and identify trends, risks and opportunities in customer and campaign data to inform strategy aligned with business objectives
• Assist marketing teams in A/B test design and execution and analysing results using statistical methods
• Ensure data quality, accuracy and consistency across all marketing sources
• Build data products that help to monitor the health of campaigns, continuously innovating on the practices and the tools we rely on to deliver the right insights at the right decision points (A/B Testing, Analysis (SQL), Visualisation (Looker, Domo), Tracking (Google Analytics), Automation (Python), AI (Gemini)).

What excites us  

Essentials:

• You have a background working in (performance) marketing analytics or a marketer looking for a more data focused role. 
• You have knowledge of common marketing measurement metrics, tools & methodology.
• You are a self-starter, focused on results, with a demonstrated background in using analytics to drive the understanding, growth, and success of marketing campaigns
• You have experience with data visualisation tools and communicating findings from complex data sets in an accessible way
• You are proficient in basic SQL

Nice to have:

• A basic knowledge of Python/R is advantageous but not essential
• You have experience leveraging AI capabilities to enhance data analysis, automate tasks, and improve decision-making processes

We don’t expect you to meet every requirement. If you’re excited by this role, we encourage you to apply.

Salary range: the expected base salary range for this position is between €45,600 - €68,400.

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.

Why Verifone

For more than 30 years, Verifone has established a remarkable record of leadership in the electronic payment technology industry. Verifone is one of the leading electronic payment solutions brands and among the largest providers of electronic payment systems worldwide.

Verifone has a diverse, dynamic, and fast-paced work environment in which employees are focused on results and have opportunities to excel. We take pride in working with leading retailers, merchants, banks, and third-party partners to invent and deliver innovative payment solutions around the world. We strive for excellence in our products and services and are obsessed with customer happiness.

Across the globe, Verifone employees are leading the payments industry through experience, innovation, and an ambitious spirit. Whether it’s developing the next generation of secure payment systems or finding new ways to bring electronic payments to emerging markets, the Verifone team is dedicated to the success of our customers, partners, and investors. It is this passion for innovation that drives every Verifone employee toward personal and professional success.

Verifone is proudly an in-office work culture as we see immense benefits to career development and business results from our colleagues being physically co-located.

What’s Exciting About the Role

Verifone is seeking a Kafka DevOps Engineer to join our Platform Engineering team. This is an operations-first role with a strong emphasis on scripting, automation, and pipeline development. You’ll be hands-on with day-to-day Kafka operations, reliability, tuning, and high availability for payment gateway solutions that process billions of transactions annually on-prem and in AWS Cloud. Beyond keeping the lights on, you’ll play a key role in building the data pipelines—of which Kafka is a core component—that power Verifone’s new AI, machine learning, and analytics initiatives. You’ll also be part of an active effort to migrate Kafka and related services to Kubernetes, giving you hands-on experience with a meaningful infrastructure modernization project. The technology footprint is broad: Redis, MongoDB, PostgreSQL, MySQL, Snowflake, and more—so you’ll grow well beyond a single-technology niche.

Key Responsibilities

Kafka Operations & Reliability

• Manage and support Apache Kafka clusters (including MSK), Kafka Connect ecosystem, and KSQL for high-throughput, fault-tolerant messaging and event streaming pipelines.
• Monitor system health, set up alerts, and drive incident response and root cause analysis (RCA).
• Handle day-to-day operational tasks including offset management, lag monitoring, consumer group management, and cluster rebalancing.
• Perform routine cluster maintenance: upgrades, configuration changes, scaling, and health checks.

Scripting, Automation & DevOps

• Develop and manage automation scripts using Python and Shell scripting to reduce manual toil and improve operational efficiency.
• Design, implement, and maintain robust CI/CD pipelines for patching automation.
• Build and maintain Infrastructure as Code (IaC) using tools such as Terraform, Ansible, or similar.
• Containerize and orchestrate workloads using Docker and Kubernetes, with the opportunity to help migrate Kafka and related services to Kubernetes.

Data Pipeline Development

• Build and optimize end-to-end data pipelines, with Kafka as a core streaming component alongside batch and ETL processes, enabling new AI, ML, and analytics use cases.
• Collaborate with development teams to implement best practices for data flow, security, scalability, and performance.
• Continuously identify and implement improvements to the software development lifecycle (SDLC).

Cloud & Infrastructure

• Manage cloud infrastructure on AWS (VMs, networking, storage, IAM, etc.).
• Support cloud migration tasks and assist in moving workloads between on-prem and cloud environments.

Required Qualifications / Skills

• 4+ years of overall engineering experience with 2+ years of hands-on experience supporting Kafka infrastructure in a large-scale production environment.
• Kafka Producer/Consumer microservices concepts and Kafka distributed architecture.
• Solid Linux fundamentals: networking basics, logs, system troubleshooting, process/memory, disk.
• Strong scripting and automation skills (Python, Bash) with a track record of reducing operational toil.
• CI/CD pipeline development and Infrastructure-as-Code experience (Terraform preferred).
• Cloud engineering skills, preferably AWS (EC2, VPC, IAM, MSK/ElastiCache, CloudWatch).
• Familiarity with observability tools (metrics/logs/tracing concepts) and incident response practices.
• Basic understanding of distributed systems tradeoffs (availability, consistency, partitions, backpressure).
• Strong communication and presentation skills with emphasis on executive communication.
• Flexible with regards to working shifts; on-call and weekends.

Preferred Skills (Highly Desired)

Data Engineering & Pipelines

• Data engineering skills including data analytics, data processing, ETL, and data lake technologies (batch and streaming, file formats like Parquet, table formats like Iceberg/Delta/Hudi, basic orchestration).
• Experience with AWS data tools (Athena, Glue, Iceberg, Redshift, etc.).
• Exposure to Kafka Streams, Apache Flink, or similar stream processing frameworks.

Database & Caching Technologies

• Operate Redis deployments for caching, ephemeral state, queues/streams, and rate limiting use cases.
• Relational DB experience: PostgreSQL and/or MySQL (indexing basics, vacuum/analyze, query plans, replication fundamentals).
• MongoDB operational familiarity (replica sets, elections, oplog basics, backup/restore).

Infrastructure & Security

• Container/Kubernetes familiarity (deployments, stateful workloads, storage classes).
• On-prem experience (VMware/KVM, storage, networking).
• Security fundamentals: least privilege, secrets management, encryption-in-transit/at-rest concepts.
• Experience working with PCI (Payment Card Industry Data Security) standards.

What We Offer

• Direct impact on Verifone’s global payment infrastructure—your work keeps billions of transactions flowing reliably every year.
• Ground-floor involvement in building the data pipelines that will drive Verifone’s AI, machine learning, and analytics strategy.
• Hands-on participation in a Kafka-to-Kubernetes migration—a resume-building modernization project from day one.
• Multi-technology exposure—Kafka, Redis, MongoDB, PostgreSQL, MySQL, Snowflake—so you grow as a well-rounded platform engineer, not a single-tool specialist.
• Mentorship from senior engineers and Kafka architects with deep production experience.
• Clear career progression path from mid-level to senior and lead engineer.
• Funded certification paths—Confluent (CCDAK, Certified Administrator), AWS (Solutions Architect, MSK Specialty), CKA—plus budget for courses and technical conferences.
• Hybrid/remote working flexibility with a collaborative team culture.
• Competitive compensation with performance-based incentives.

Our Commitment

Verifone is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Verifone is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

We are seeking an experienced Senior Project Manager with a background in Business Analysis and/or Product Management to lead strategic business initiatives. This role is responsible for the end-to-end execution of projects focused on analyzing, planning, implementing, and automating business processes. The ideal candidate combines project management expertise with analytical skills to drive business process improvements at both departmental and company levels.

Key Responsibilities

• Lead and coordinate multiple projects simultaneously across different departments, ensuring timely delivery within scope and budget
• Own end-to-end project planning, including solution design, budgeting, resource allocation, and risk management
• Conduct in-depth analysis of workflows and business processes to identify optimization opportunities and translate them into actionable project requirements
• Drive business process improvements through research, process modeling, data analysis, and gap analysis
• Communicate effectively with stakeholders throughout the project lifecycle - gathering requirements, reporting progress, presenting results, and managing expectations
• Lead change management efforts, ensuring smooth transitions and stakeholder engagement during implementation
• Coordinate with cross-functional teams to ensure the successful integration of business systems, processes, and technology solutions

Qualifications

• 4+ years of proven project management experience
• Proven experience as a Business Analyst or Product Manager
• Proven experience in managing digital and operational business process improvement projects
• Hands-on experience in business process analysis and workflow optimization with a proven track record of implementing improvements directly into products or operational processes
• Experience managing cross-functional teams and collaborating with business and technical stakeholders
• Fluency in English (Upper-Intermediate or Advanced level)
• Experience implementing AI into products and/or business processes with measurable results is a plus
• Proficiency in no-code/low-code tools (n8n, Zapier, Make, Bubble, Bolt, etc.) is a plus

What We Offer

• Opportunity to shape the backbone systems of a modern, data-driven digital company.
• Autonomy to lead meaningful projects from ideation to impact.
• A collaborative, innovation-first environment that values initiative and experimentation.
• Reduced working hours on Fridays during the summer.
• Schedule: Monday–Friday, 1:00/2:00 PM – 9:00/10:00 PM EET.

Why Join Us

You’ll be at the intersection of technology, process innovation, and business growth - building systems that empower our teams to work smarter, faster, and more collaboratively. If you’re a strategic thinker who loves turning complexity into clarity and ideas into scalable solutions, we’d love to meet you.

Inbank is a financial technology company with an EU banking license that connects merchants, consumers, and financial institutions on its next-generation embedded finance platform. Our financing solutions are embedded seamlessly into the shopping journey of 6,000+ retailers. This helps our merchant partners grow their businesses, while end customers benefit from a frictionless shopping experience wherever they are. With a focus on innovation and growth, we are looking for talented people to join our team of 440+ working across our offices in Estonia, Latvia, Lithuania, Poland, and the Czech Republic.

Due to our growth ambitions, we are looking for a talented Credit Risk Underwriting Modeller to join our Riga office. In this hands-on role, you will help improve how we assess credit risk and ensure the profitability of our products by developing and refining statistical models used in credit decisioning.

You will work closely with credit risk specialists and technology teams, combining data, business understanding, and modeling techniques to build effective underwriting solutions. In this role, your work will have a direct impact on business performance. By improving credit decision models, you will contribute to better risk management and stronger profitability—playing a key role in shaping data-driven decisions across the organization.

What will you be doing?

• Develop, improve, and maintain statistical models used in credit underwriting.
• Own the end-to-end modeling process: from data collection and preparation to model development, validation, and monitoring.
• Analyze and combine internal and external data sources to enhance model performance.
• Continuously monitor models and optimize them for accuracy, risk management, and profitability.
• Collaborate with the technology team to improve automated credit decision systems (decision engine, data integrations, workflows).
• Work closely with credit risk underwriters and product managers to translate business needs into effective modeling solutions.
• Prepare analytical reports and ensure clear model documentation and transparency.
• Stay up to date with industry trends and best practices in credit risk modeling.

 Ideally, you would have:

• 3+ years of proven experience in a similar role (statistical, predictive, or data modeling); experience in fintech or banking is a plus.
• Solid understanding of statistical methods and machine learning techniques, with the ability to apply them in practice.
• Strong analytical mindset and confidence working with complex, real-world datasets.
• Strong SQL skills, with hands-on experience in data extraction and manipulation.
• Proficiency in Python, R, or similar tools.
• Ability to work independently while collaborating effectively with cross-functional teams.
• Clear communication skills in English, both written and spoken.

What you’ll get in return?

• The offered salary is within the range of €4,000–€5,000 gross per month, along with a comprehensive benefits package.
• Wellbeing support through sports compensation or additional health insurance to help you stay active and healthy.
• A 6-week paid sabbatical after four years, recognising strong performance and long-term contribution.
• A dynamic and inspiring work environment where you’re encouraged to grow and take ownership of your work.
• Flexibility through a hybrid and autonomous way of working, built on trust and accountability.
• The opportunity to collaborate with talented international colleagues across multiple markets.
• Regular team events and additional perks that make work more enjoyable and help celebrate successes together.

Sounds like a fit?

Apply, and our recruitment team will be in touch. If you’re unsure but curious, apply anyway - we’re happy to explore together.

Payment Intelligence

Our mission is to make GoCardless the best way to pay and be paid. Our ambition is to dramatically improve payment performance and safeguard our customers from bad outcomes like payment fraud and failures. You will help find data opportunities and areas to improve our payment intelligence products. You should be comfortable with large data sets, customer data, and machine learning principles. You’ll work alongside Product Managers, Engineers and Data Scientists in our two core Payment Intelligence teams to provide critical insights and help drive product direction.

Our existing Payment Intelligence Products are already one of the key reasons why customers choose GoCardless. These include Protect+, which defends customers from fraud, and Success+, which helps customers intelligently recover failed payments. You will need to own our understanding of these products and identify insights and opportunities to help us develop new intelligent features.

What You'll Do

At GoCardless analytics is at the core of everything we do and drives business performance through data insight. You will play a critical role partnering closely with stakeholders across the business (including product, operations, marketing, and commercial teams) in order to deliver actionable insights to influence decisions at every level of the organisation. The role is focussed on identifying value and driving change throughout the business derived from insights. Your insights will be turned into actions that will help drive the future of GoCardless. You will act as the bridge between the data, technical and business stakeholders informing strategic plans and will own and evolve a suite of reports designed to give a wide range of stakeholders access insights. 

• Own and iterate on experiments to generate user insight and drive business metrics, allowing the team to quickly take action on business opportunities.
• Define how we quantitatively evaluate success, setting KPIs, designing tracking to measure what really matters, delving into the leading indicators of user behaviour
• Influence the organisation to increase Product Data coverage and implement user tracking best practices - acting as a mentor to guide other members of the organisation to become data driven
• Build models of user-segmentation, customer lifetime value etc in order to inform strategic product & commercial decisions
• Continuously innovate on the practices and the tools we rely on to deliver the right insights at the right decision points (A/B Testing, Analysis (SQL), Visualisation (Looker), Tracking (Amplitude), Automation (Python), AI (Gemini)

What Excites You

• Become a strategic partner and advisor for the business: you like to proactively seek out gaps in our product capabilities, suggest areas of improvement based on tangible data, as well as owning processes to run and improve testing from the tracking point of view when developing new features. 
• Act as a catalyst for change across the organization, driving the evolution of our data analytics standards, internal processes, and overall product data strategy to ensure scalability and operational excellence.
• Translate complex technical findings into compelling, high-impact narratives. You will bridge the gap between technical data and commercial strategy, influencing product roadmaps and executive decision-making across the entire organization.
• Stay current with AI and data trends to solve real-world problems. You like to leverage these technologies to enhance the payment experience, as well as to optimize data analysis, and deliver high-impact insights and strategic recommendations across the business.
• Unlocking new layers of payment performance, from uncovering new fraud vectors to maximizing success rates
• Serve as a cross-functional mentor, championing a data-driven mindset and elevating the analytical capabilities of team members throughout the company.

What Excites us

• You have a background working in similar fast paced product-driven teams and are great at communicating insights to a range of audiences, including senior stakeholders, to drive data-informed product decisions
• You are a self-starter, focused on results, with a demonstrated background in using analytics to drive the understanding, growth, and success of a product
• You have extensive experience with data visualisation tools mentioned above and develop compelling visualisations which influence decision making and business understanding
• You have advanced SQL skills and intermediate Python skills & have experience leveraging AI capabilities to enhance data analysis, automate tasks, and improve decision-making processes
• You have a background working in similar fast paced teams and are great at communicating insights to a range of audiences, including senior stakeholders, to drive data-informed decisions.
• You are solution-oriented and able to own projects from start to finish. You are comfortable motivating stakeholders across the business and negotiating timelines to unblock yourself and make things happen!

Salary range: the expected base salary range for this position is between €32,000 - €48,000.

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.

Payment Intelligence

Our mission is to make GoCardless the best way to pay and be paid. Our ambition is to dramatically improve payment performance and safeguard our customers from bad outcomes like payment fraud and failures. You will help find data opportunities and areas to improve our payment intelligence products. You should be comfortable with large data sets, customer data, and machine learning principles. You’ll work alongside Product Managers, Engineers and Data Scientists in our two core Payment Intelligence teams to provide critical insights and help drive product direction.

Our existing Payment Intelligence Products are already one of the key reasons why customers choose GoCardless. These include Protect+, which defends customers from fraud, and Success+, which helps customers intelligently recover failed payments. You will need to own our understanding of these products and identify insights and opportunities to help us develop new intelligent features.

What You'll Do

At GoCardless analytics is at the core of everything we do and drives business performance through data insight. You will play a critical role partnering closely with stakeholders across the business (including product, operations, marketing, and commercial teams) in order to deliver actionable insights to influence decisions at every level of the organisation. The role is focussed on identifying value and driving change throughout the business derived from insights. Your insights will be turned into actions that will help drive the future of GoCardless. You will act as the bridge between the data, technical and business stakeholders informing strategic plans and will own and evolve a suite of reports designed to give a wide range of stakeholders access insights. 

• Own and iterate on experiments to generate user insight and drive business metrics, allowing the team to quickly take action on business opportunities.
• Define how we quantitatively evaluate success, setting KPIs, designing tracking to measure what really matters, delving into the leading indicators of user behaviour
• Influence the organisation to increase Product Data coverage and implement user tracking best practices - acting as a mentor to guide other members of the organisation to become data driven
• Build models of user-segmentation, customer lifetime value etc in order to inform strategic product & commercial decisions
• Continuously innovate on the practices and the tools we rely on to deliver the right insights at the right decision points (A/B Testing, Analysis (SQL), Visualisation (Looker), Tracking (Amplitude), Automation (Python), AI (Gemini)

What Excites You

• Become a strategic partner and advisor for the business: you like to proactively seek out gaps in our product capabilities, suggest areas of improvement based on tangible data, as well as owning processes to run and improve testing from the tracking point of view when developing new features. 
• Act as a catalyst for change across the organization, driving the evolution of our data analytics standards, internal processes, and overall product data strategy to ensure scalability and operational excellence.
• Translate complex technical findings into compelling, high-impact narratives. You will bridge the gap between technical data and commercial strategy, influencing product roadmaps and executive decision-making across the entire organization.
• Stay current with AI and data trends to solve real-world problems. You like to leverage these technologies to enhance the payment experience, as well as to optimize data analysis, and deliver high-impact insights and strategic recommendations across the business.
• Unlocking new layers of payment performance, from uncovering new fraud vectors to maximizing success rates
• Serve as a cross-functional mentor, championing a data-driven mindset and elevating the analytical capabilities of team members throughout the company.

What Excites us

• You have a background working in similar fast paced product-driven teams and are great at communicating insights to a range of audiences, including senior stakeholders, to drive data-informed product decisions
• You are a self-starter, focused on results, with a demonstrated background in using analytics to drive the understanding, growth, and success of a product
• You have extensive experience with data visualisation tools mentioned above and develop compelling visualisations which influence decision making and business understanding
• You have advanced SQL skills and intermediate Python skills & have experience leveraging AI capabilities to enhance data analysis, automate tasks, and improve decision-making processes
• You have a background working in similar fast paced teams and are great at communicating insights to a range of audiences, including senior stakeholders, to drive data-informed decisions.
• You are solution-oriented and able to own projects from start to finish. You are comfortable motivating stakeholders across the business and negotiating timelines to unblock yourself and make things happen!

Salary range: the expected base salary range for this position is between €32,000 - €48,000.

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).

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.