Checkout.com is one of the most exciting and valuable fintechs in the world, with our Series D taking our valuation to $40 billion. 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, Binance, 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 number 9 on the Forbes Cloud 100 list and on Glassdoor’s list of Top 10 fintechs to work for. 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. So, join us to build tomorrow, today.
About the role
This role will see you join Checkout’s Data Platform team, where you’ll work on Machine Learning (ML) systems for providing near-real-time transaction fraud predictions.
Checkout’s Data Platform team is composed of engineers who build systems to enable product teams to be passionate about data and maximise the amount of time they spend solving business problems rather than data infrastructure/implementation ones.
You’ll join an ambitious team of data scientists and engineers who are working to deliver fraud detection ML models to Checkout.com’s merchants, at scale – with the plan of generalising this work to other ML use-cases. Your work will significantly move the needle within a product area that has high strategic importance to Checkout.com.
Maintain distributed systems for training, deploying, and monitoring ML models, at scale.
Write high-performance, production-ready code (mostly Python) for model training and deployment.
Develop batch and real-time feature store ingestion to make ML features available offline (for training) and online (in production).
Constructively review the work of others, and mentor other members of the team.
Give to discussions on system design and team strategy.
Participate in out of hours support.
Strong engineering background with experience working on production systems.
Experience working with, and scaling, ML systems.
Theoretical understanding of ML methods, particularly ensemble decision trees.
Able to write simple, production-ready, Python code.
Experience maintaining RESTful ML model APIs.
Experience with workflow management tools (e.g. Airflow, Metaflow, Prefect).
Experience with SQL and NoSQL databases.
Experience working with Docker for development and deployment.
Experience using AWS as a cloud provider.
Familiar with distributed data processing tools (e.g. Spark, Dask, Hadoop).
Familiar with the unix shell, and shell scripting.
Consistent record working in technical teams.
Nice to have:
Experience with stream processing technologies (e.g. Kinesis, Kafka).
Familiar with profiling code and performance optimizations.
Open-source contributions and/or personal software projects.
Experience with ETL tools like dbt.
What we stand for
At Checkout.com, everything starts with our values, including the experience we offer our people.
We supercharge your professional growth with career development programs and leadership training. You can learn your way, with tailored pathways and online platforms. And be inspired at relevant conferences.
We don’t stop at ‘good’ here. We strive for excellence amongst our teams every day and recognize colleagues who take it to the next level through our quarterly peer-nominated Hero awards.
We’re proud of our global connections and inclusive environment. So we champion this through our colleague-led community groups and celebrate many cultural events together.
Want to see us in action?
More about Checkout.com
Our technology makes payments seamless. We provide the fastest, most reliable payments in more than 150 currencies, with in-country acquiring, world-class fraud filters and reporting, through one API. And we can accept all major international credit and debit cards, as well as popular alternative and local payment methods. Checkout.com launched in 2012, and we now have a team of 1800 people across 19 international offices. To date, we’ve raised a total of $1.8 billion, with our Series D valuing us at $40 billion.
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.