Job Description

Company Description

Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We\'re the strategic payments partner for some of the best known fast-moving brands globally such as Wise, Hut Group, Sony Electronics, Homebase, Henkel, Klarna and many others. Purpose-built with performance and scalability in mind, our flexible cloud-based payments platform helps global enterprises launch new products and create experiences customers love. And it\'s not just what we build that makes us different. It\'s how.
We empower passionate problem-solvers to collaborate, innovate and do their best work. That\'s why we\'re on the Forbes Cloud 100 list and a Great Place to Work accredited company. And we\'re just getting started. We\'re building diverse and inclusive teams around the world - because that\'s how we create even better experiences for our merchants and our partners. And we need your help. Join us to build the digital economy of tomorrow.



About the Role
Checkout.com is looking for a 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 Checkout.com\'s merchants use to make smart payment routing decisions based on their risk appetite.
You\'ll join an enterprising team of data scientists and engineers who are working to deliver fraud detection ML models at scale. Your primary responsibility will be ML research. Your work will significantly move the needle within a product area that has high strategic importance to Checkout.com.

Key Responsibilities

• Conduct greenfield research into ML (or other statistical) approaches for detecting fraud. This will involve reading and implementing papers.
• Design, implement, and interpret experiments to produce practical insights and improve model performance.
• Report and present research findings to technical and non-technical audiences, verbally and in writing.
• Write high-quality Python for feature engineering and model training.
• Drive the collection of new data and enrichment of existing data sources.

Qualifications

About You

• PhD (or a minimum of Masters with research experience in industry) in a STEM subject (i.e. computer science, mathematics, physics, etc.).
• At least 2 years experience developing machine learning models to solve business problems, with a primary emphasis on ML research.
• Experience with distributed computing technologies (e.g. Spark, Dask) for processing large data.
• Strong understanding of: machine learning, probability and statistics.
• Experience applying scientific methods and thoughtful experimental design.
• Able to write high quality Python and SQL.

Nice to have

• Experience in fintech and/or payments.
• Experience with AWS or at least another common cloud platform (GCP/Azure).
• Familiar with the unix shell and shell scripting (for automating tasks).

Additional Information

Apply without meeting all requirements statement
If you don\'t meet all the requirements but think you might still be right for the role, please apply anyway. We\'re always keen to speak to people who connect with our mission and values.
We believe in equal opportunities
We work as one team. Wherever you come from. However you identify. And whichever payment method you use.
Our clients come from all over the world - and so do we. Hiring hard-working people and giving them a community to thrive in is critical to our success.
When you join our team, we\'ll empower you to unlock your potential so you can do your best work. We\'d love to hear how you think you could make a difference here with us.
We want to set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. We\'ll be happy to support you.
Take a peek inside life at Checkout.com via

• Our Culture video https://youtu.be/BEwnpHuadSw
• Our careers page https://www.checkout.com/careers
• Our LinkedIn Life pages bit.ly/3OaoN1U
• Our Instagram https://www.instagram.com/checkout_com/

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