About Us

Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Acer, Gucci, Lorna Jane, GoPro, and many more.

We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day. 

About the Role

The Data Science department plays a pivotal role in our company, generating value to Riskified by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.

What You'll Be Doing

• Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
• Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
• Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
• Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
• Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
• Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
• Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
• Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

Qualifications

• B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field
• 3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production.
• Strong understanding and practical experience with various machine learning algorithms.
• Proficiency in Python, Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis
• Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design
• Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions
• Proficiency in data visualization libraries, to create meaningful visual representations of complex data
• Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment

• Experience in the fraud domain
• Experience with Airflow, CircleCI, PySpark, Docker and K8S

Life at Riskified

We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking.

We’re looking for bright, driven, and passionate people to grow with us.

Some of our Lisbon Benefits & Perks:

• Hybrid mode of work
• Flexible schedule
• Healthcare benefits
• Fully-stocked kitchens
• Benefits package per month—per your choice, e.g., work-from-home equipment, gym membership, wellbeing activities, and more.
• Wellness program
• Celebrations and activities
• Team events
• Happy hours
• Awesome Riskified gifts and swags
• Volunteer programs
• Personal development
• Global onboarding
• Role-based technical skills training
• Full access to Udemy

In the News

C-Tech: We need to find the balance between leveraging innovative AI solutions and using them cautiously

Built In: How We Built This: A Riskified Technologist Unpacks The Company’s Beacon Technology

Globes: Riskified is among Israel’s fastest growing companies  

Yahoo: Riskified Earns "Top Rated" Award Across Four TrustRadius Solution Categories

Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.

Let's start with the role

As a GenAI Senior Data Scientist, you will be at the forefront of our AI developments,  analyzing data, building Gen AI powered applications and/or agentic architectures. You will be responsible for selecting the right LLMs, performing prompt engineering and model fine-tuning to support our AI products. You will collaborate closely with cross-functional tech teams to deliver impactful, production-grade AI solutions. The ideal candidate has a deep understanding of LLMs and agentic architectures, along with proven experience building and deploying such applications in production environments.

As a GenAI Senior Data Scientist you will:

• Translate product requirements to AI problems and identify areas where AI can drive the most business impact;
• Analyze data to uncover significant patterns and generate actionable insights;
• Architect agentic and GenAI systems;
• Select appropriate models for the right tasks and tune their performance;
• Perform exploratory data analysis (EDA and feature engineering to support the modeling process;
• Apply best practices on model selection, parameter tuning etc.;
• Run comparative experiments for model training;
• Analyze ML metrics to evaluate different potential solutions;
• Manage the full lifecycle of AI features, from data collection to model design and to implementation and optimization in production;
• Mentor and guide junior members, sharing knowledge and leading complex projects. 

What you’ll bring:

Must have:

• Hands on experience with GenAI and Agentic applications;
• Extensive hands-on experience in delivering AI driven products to production;
• Experience in scaling and optimisation of AI applications;
• Knowledge of machine learning algorithm and respective theory;
• Knowledge of the Python machine learning ecosystem and solid software background in OOP;
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

Nice to have:

• Experience with Big Data tools  (Spark/PySpark) and cloud environment, ideally Azure / Databricks;
• Previous experience in LLM fineturing;
• Previous experience with LLM serving;
• Knowledge of Deep learning. 

Kaizen Gaming Perks

• 🕑 Hybrid way of working
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay & bonus scheme
• ⭐Developmental 360° feedback framework
• 💰 Monthly meal allowance
• 👩‍⚕️ Private health insurance for you and your family
• 📚 Unlimited access to Udemy & continuous training
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-ap1

Let's start with the role

At Kaizen, our aim is to make data driven decisions in order to automate our servicers while also focusing on offering tailored customer experiences. Our machine learning team is dedicated towards this mission by building a variety of models, from binary classification tasks up to recommendation systems. We focus on transforming business needs into production applications and we cover a wide range of business sectors utilizing different data types and handling a broad project diversity. 

Our teams comprise of three different roles, data scientists, machine learning engineer and data engineers so that they include the full skillset to deliver projects to production.

We are currently looking for data scientists in all levels to join our teams. The role should combine strong knowledge of machine learning algorithms, analytical skills, experimental design etc. to support the model development process.

• Translate business requirements to machine learning problems;
• Perform EDA and feature engineering;
• Run comparative experiments for model training;
• Implement best practices on model selection, parameter tuning etc.

What you’ll bring

• A background in Computer Science, Statistics, Math or related field;
• Strong knowledge of machine learning algorithm and respective theory;
• 2-8 years of hands-on experience in delivering machine learning models to production;
• Knowledge of the Python machine learning ecosystem;
• Experience with Spark (PySpark);
• Solid software background in OOP;
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

Nice to have

• Experience with Azure / Databricks;
• Knowledge of Deep learning;
• Experience in recommendation systems.

#Artificial Intelligence (AI) #Machine Learning (ML) #Data Science (DS)

Kaizen Gaming Perks

• 🕑 Hybrid way of working
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay & bonus scheme
• ⭐Developmental 360° feedback framework
• 💰 Monthly meal allowance
• 👩‍⚕️ Private health insurance for you and your family
• 📚 Unlimited access to Udemy & continuous training
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Remote
• #LI-PROMOTE

We're a leading SaaS provider revolutionising how fintech companies navigate complex regulatory landscapes. Our platform powers compliance and risk management for hundreds of innovative financial services companies, from emerging startups to established enterprises. We believe in empowering our teams to solve meaningful problems and create exceptional value for our customers.

Role Summary

As a Senior Data Scientist at ComplyAdvantage, you will lead the development and refinement of sophisticated data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, where you will spend 80% of your time conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value over 3-6 month horizons. In addition to driving deep-dive R&D, you will provide expert advisory support and technical leadership to Product and Engineering teams. By leading AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features while mentoring more junior members of the tribe.

Key Responsibilities

• Lead R&D in GenAI and Agentic AI: Design and prototype high-impact, novel solutions for financial crime detection, focusing on multi-agent systems and RAG architectures built on foundational LLM frameworks.
• Drive Production Excellence: Partner with Engineering and Product leadership to architect and oversee the integration of AI components into core product features. You will define the standards for reliability, scalability, and ethical AI performance, ensuring research prototypes transition into robust, production-grade solutions.
• Establish Evaluation Frameworks: Lead the development of robust evaluation methodologies for LLM and agentic AI systems, defining industry-standard metrics for task completion, reasoning accuracy, and system reliability.
• Evaluate Model Context Protocol (MCP): Research applications to connect our AI systems with external data sources and tools, providing strategic recommendations for engineering implementation.
• Strategic Data Insights: Conduct advanced exploratory analysis across multiple data sources to uncover insights that directly influence product development decisions and agent behavior.
• Research & Innovation: Continuously research and evaluate emerging tools and best practices in data science and Agentic AI to keep ComplyAdvantage at the forefront of the field.
• Technical Leadership & Mentoring: Engage across multi-disciplinary teams to share expertise, perform code reviews, and provide career development support to junior data scientists.

Required Qualifications

• MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
• 4-7 years of professional experience in data science or machine learning, with a demonstrable impact on production systems.
• Expert-level proficiency in Python, including the core data science ecosystem such as Pandas, NumPy, and Scikit-learn.
• Deep experience with modern ML frameworks (e.g., TensorFlow, PyTorch) for advanced research and prototyping.
• Strong expertise in Agentic AI and LLMs: Advanced knowledge of agentic AI frameworks (e.g., LangChain, Pydantic AI) and experience optimising retrieval systems like RAG.
• Experience with Distributed Computing: Practical knowledge of platforms like Spark or Dask for large-scale data analysis.
• Technical Leadership: Proven track record of leading technical research projects with successful production outcomes and communicating complex concepts to diverse audiences.

Preferred Qualifications

• Experience delivering machine learning solutions and integrating into data pipelines.
• Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
• Experience working with or evaluating multi-agent systems or complex GenAI workflows.

What Success Looks Like

• In 90 days: You have successfully onboarded, mastered our data landscape, and begun contributing to active research projects while building relationships with key stakeholders.
• In 6 months: You have delivered your first significant research project with measurable impact and established yourself as a technical leader and effective mentor.
• In 12 months: You have led multiple successful R&D initiatives that have shaped our technical roadmap and been recognized as a subject matter expert who empowers other teams.

About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.

What’s in it for you? 

• Equity as we want you to have a part of what we are building 
• Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
• Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best 
• We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
• You will also get a new starter budget to kit out your home office 
• Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve 
• Annual learning budget (prorated based on start date) to drive your performance and career development 

Role Summary

As a Data Scientist at ComplyAdvantage, you will develop and refine data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value. In addition to deep-dive R&D, you will provide advisory support to Product and Engineering teams. By investing in AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features.

Key Responsibilities

• Advance R&D in GenAI and Agentic AI: Develop high-impact prototypes for financial crime detection, leveraging multi-agent systems and RAG architectures built on foundational LLM frameworks.
• Contribute to Core Solutions: Collaborate with Engineering and Product to integrate and optimise AI components and frameworks into existing and new product features, ensuring reliability, scalability, and ethical performance in production.
• Evaluate LLM-based Systems: Contribute to the development and implementation of robust evaluation methodologies for LLM and agentic AI based systems, tracking key metrics related to task completion, reasoning accuracy, tool effectiveness, and overall reliability.
• Evaluate Model Context Protocol (MCP) applications: Connect our AI systems with external data sources and tools and provide recommendations for engineering implementation
• Data Understanding: Develop a solid understanding of our existing data sources, identifying challenges and suggesting potential improvements.
• Data Analysis: Use exploratory data analysis and data mining techniques to identify actionable insights for product improvement, including patterns that can inform and refine agent behavior and prompt engineering strategies.
• Research & Innovation: Continuously research and evaluate emerging tools, technologies, and best practices in data science, especially within the rapidly evolving field of Agentic AI, to keep ComplyAdvantage at the forefront.
• Cross-Functional Collaboration: Engage effectively with multi-disciplinary teams to actively share best practices, expertise and inspire innovation to foster an AI-first culture across the organization.
• Visualization & Roadmapping: Provide clear data insights and visualizations that will act as a basis for new ideas to be integrated into our product roadmap.

Required Qualifications

• MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
• 2-4 years of professional experience in data science or a related field, with a demonstrated ability to contribute to impactful data-driven solutions.
• Proficiency in Python, including experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
• Hands-on experience with modern machine learning frameworks such as TensorFlow or PyTorch.
• Familiarity with the foundational concepts of agentic AI and large language models (LLMs). This can be professional or through personal research.
• Basic understanding of popular agentic AI frameworks (e.g., LangChain, Pydantic AI).
• Knowledge of general evaluation techniques for AI models and an eagerness to learn and apply methods specific to agentic systems.
• Ability to communicate complex technical concepts effectively to a variety of stakeholders.
• Strong passion for data and solving challenging real-world problems using algorithms.

Preferred Qualifications

• Prior experience contributing to the deployment and integration of machine learning models into production data pipelines.
• Exposure to Big Data platforms such as Spark.
• Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
• Experience working with or evaluating multi-agent systems or complex AI workflows.

What Success Looks Like

• In 90 days: You have successfully onboarded, gaining a clear understanding of our data landscape and current AI frameworks. You are actively contributing to R&D experiments and have established collaborative working relationships with peers in Engineering and Product.
• In 6 months: You have delivered your first significant R&D prototype or technical evaluation. You have begun contributing to our AI Enablement workstreams, perhaps by authoring a technical blog post or internal guide that translates your research findings into actionable knowledge for the wider team.
• In 12 months: You have completed multiple R&D initiatives that have shaped our technical roadmap. You are recognized for empowering other teams through your advisory support and quantitative expertise, consistently providing the "AI-first" insights that help Engineering and Product teams scale high-impact features.

About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.

What’s in it for you? 

• Equity as we want you to have a part of what we are building 
• Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
• Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best 
• We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
• You will also get a new starter budget to kit out your home office 
• Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve 
• Annual learning budget (prorated based on start date) to drive your performance and career development 

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.

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

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: £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 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.