Company Description
We’re Checkout.com – you might not know our name, but companies like eBay, ASOS, Klarna, Uber Eats, and Sony do. That moment when you check out online? We make it happen.
Checkout.com is where the world checks out. Our global network powers billions of transactions every year, making money move without making a fuss. We spent years perfecting a service most people will never notice. Because when digital payments just work, businesses grow, customers stay, and no one stops to think about why.
With 19 offices spanning six continents, we feel at home everywhere – but London is our HQ. Wherever our people work their magic, they’re fast-moving, performance-obsessed, and driven by being better every day. Ideal. Because a role here isn’t just another job; it’s a career-defining opportunity to build the future of fintech.
Job Description
As a Data Science Manager in the Payments Performance pillar you will lead a team of 5-8 smart and ambitious data scientists that drive the success of our machine learning solution for payment optimization in our London office. We are looking for someone passionate about building high-performing teams that consistently deliver value in a rapidly evolving area.
You’ll be working with data scientists, analysts and engineers on creating technical solutions and communicating effectively across teams and senior leadership. Your leadership will be pivotal for translating complex problems into actionable roadmaps that ultimately impact millions of online shoppers worldwide.
How you’ll make an impact
- Drive the roadmap and priorities for your team, and work with many leaders across the company to enhance our ability to deliver best-in-class performance, through ML.
- Build the brain behind mission-critical products that make real-time decisions during the payment processing flow.
- Collaborate with stakeholders across the organization such as engineering, analytics, operations and product.
- Manage a high-performing team of data scientists, supporting them to achieve a high level of technical excellence and advance in their careers.
What We’re Looking For
- You have at least 2 years of direct management experience leading data science and ML teams in a complex domain.
- Excellent communication skills, ability to simplify machine learning concepts and data analyses for broad audiences.
- You’ve managed teams that have built and shipped machine learning systems and data products at scale.
- You work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs.
- You thrive on a high level of autonomy and responsibility.
- You foster a healthy, inclusive, challenging, and supportive work environment.
- Growth mindset, always on the lookout for stretch challenges.
- Experience dealing with data from complex domains (FinTech, Fraud Detection or Payments Processing are a significant plus)
Bring all of you to work
We create the conditions for high performers to thrive – through real ownership, fewer blockers, and work that makes a difference from day one.
Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity – and where your growth is in your hands.
We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.
It’s important we 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.
Life at Checkout.com
We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.
Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us.
For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram
