Senior Data Scientist - Fraud Detection

London /
Technology – Business Intelligence /
Permanent Full-time
About us

Launched in 2012, is a leading international provider of online payment solutions. is built on 100% proprietary technology and handles every part of the payment process, providing complete transparency across the entire payment value chain.

We currently process 150+ currencies and offer access to all international cards and popular local payment methods to merchants through one integration.

Customers in our portfolio include international businesses like Samsung, Transferwise, Hopper, Virgin and Adidas. Our mission is to partner with smart businesses to optimise their payments, increase revenue and meet the dynamic needs of their customers. 

We are building a unique work environment where our people aspire to solve complex problems and deliver valuable solutions. We believe that excellence can be achieved through a dynamic culture driven by collaboration and teamwork.

In May 2020, we completed a $150m Series B funding round, tripling our valuation to $5.5bn.

Senior Data Scientist at is looking for an experienced data scientist to work on research and development of Machine Learning (ML) models for fraud detection. These algorithms will be deployed to provide near-real-time transaction risk predictions, which’s merchants use to make smart payment routing decisions based on their risk appetite.

You will join an ambitious team of data scientists and engineers who are working to deliver fraud detection ML models to’s merchants, at scale. Your work will significantly move the needle within a product area that has high strategic importance to

About You:

    • At least 4 years experience applying ML to solve real-world problems
    • Experience working on machine learning for fraud detection
    • Strong expertise in: machine learning, probability, statistics
    • Strong familiarity with decision tree ensembles
    • Experience applying scientific methods and thoughtful experimental design
    • Familiar with distributed cluster-computing (e.g. Spark, Dask, Hadoop)
    • Solid software engineering skills and able to write high-quality Python code
    • Experience working with scientific Python stack (e.g. pandas, scikitlearn, XGBoost, SciPy)
    • Experience with SQL databases and key-value stores (NoSQL)
    • Experience with Docker (docker-compose) for development and deployment
    • Experience with AWS or at least another common cloud platform (GCP/Azure)
    • Familiar with the unix shell, and shell scripting (for automating tasks)
    • PhD/MSc in Machine Learning or other STEM field

    • Don't meet all the requirements? Please still apply if you think you are the right person for the position. We are always keen to speak to people who connect with our mission and values.

What you will be doing:

    • Lead ML feature engineering efforts through scientific research
    • Design and implement experiments to produce actionable insights and improve model performance
    • Collaborate with other data scientists and engineers to productionise ML features/models
    • Write high-quality Python for feature engineering and model training
We are always looking for great people so if you don’t see a role here that fits you but you want to work with us, please send us your CV and a cover letter explaining the kind of role you are searching for and we will contact you. is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience, skills and personality. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief. Due to the numerous amount of application received, only the ones corresponding to this job profile will be contacted. If you have not been contacted within 3 weeks please deem your application as unsuccessful.

We are committed to protecting and respecting your privacy. We will only process and retain your information as necessary for the purposes of progressing your application or as required by applicable laws and regulations. We may also collect personal information about you through the application and recruitment process, either directly from you or from third-parties (employment agencies, recruitment websites, former employers, credit reference agencies or other background check agencies). In limited circumstances, we may transfer your information to the following countries outside the EU, while making sure your personal data is treated with the same level of protection offered in the EU. Please refer to our Privacy Policy ( for further information about how your data is being collected, processed and retained at