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.

Check all associated application documentation thoroughly before clicking on the apply button at the bottom of this description.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.Job Description We're on the lookout for a mid-level

Data Scientist

to join our

Acceptance Rates

team, working on end-to-end research and development of Machine Learning models to optimise the payment performance of our merchants.You'll be responsible for continually improving existing models and identifying new opportunities to apply Machine Learning to solve real world problems, using cutting-edge approaches such as Reinforcement Learning.The work this team does has a proven track record of moving the needle within a product area that has high strategic importance to Checkout.com, so there's huge opportunity for tangible impact.Key Responsibilities:

You will be expected to make substantial contributions to the research & development of new ML models.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.Qualifications At least 2 years experience developing machine learning models to solve business problems.Strong understanding of: machine learning, probability and statistics.Experience applying scientific methods and thoughtful experimental design.Able to write high quality Python code.Experience with SQL databases.Nice to have Experience in Financial Services/Fintech or Payments.Familiar with distributed general-purpose cluster-computing (e.g. Spark, Dask, Hadoop).Experience with Docker.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

Hybrid Working Model:

All of our offices globally are onsite 3 times per week (Tuesday, Wednesday, and Thursday). We’ve worked towards enabling teams to work collaboratively in the same space, while also being able to partner with colleagues globally. During your days at the office, we offer amazing snacks, breakfast, and lunch options in all of our locations.We believe in equal opportunitiesWe 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.

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