Senior Product Data Scientist London

Checkout Ltd
London
2 weeks ago
Create job alert

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.

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. 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. Join us to build the digital economy of tomorrow.

Job Description

As a Senior Product Data Scientist, you'll work as part of a cross-functional team alongside product managers, designers, and software and analytics engineers, using data and your expertise to influence and drive the strategy of our products. You'll help define how we measure the success of our products, collaborate with engineers on how we collect data, design and help build reports/dashboards, and run analyses to find product improvement opportunities. You'll be a co-owner of a product, driving it to success in partnership with other cross-functional team members.

You'll also be part of the broader data function, a team of Data Engineers, Analytics Engineers, Data Scientists, and Data Product Managers.

We're a new but highly visible function within Checkout.com, so this is an exciting opportunity to drive a positive impact.

How you’ll make an impact:

  1. You'll be responsible for analytics of a product domain. You'll define, measure, and present metrics, deliver actionable insights.
  2. Contribute product roadmaps through data-based recommendations and continuously define high-impact areas for improvement.
  3. Working closely with Data Analytics Engineers and Software Engineers to make sure we collect and model the right data to produce relevant business insights.
  4. Foster data culture across products and technology by actively sharing insights and ideas and building positive relationships with colleagues.
  5. Build experiments and analysis frameworks to quantify the ROI of product development.
  6. Lead by example your team and the broader data community to apply best practices in analytics from data collection to analysis.

Qualifications

  1. Strong communicator, you're able to explain complex technical topics to non-technical team members.
  2. Experience conducting experiments, building measurement frameworks, and validating the results with relevant quantitative methods.
  3. Strong analytical mind and demonstrable experience in converting ambiguous problems into structured and data-informed solutions.
  4. Excellent data interrogation skills with SQL.
  5. Knowledge of applied statistics (e.g., hypothesis testing, regression).

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 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.

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior/Lead Data Scientist - Talent Community

Senior Data Scientist

Senior Data Scientist, Customer Analytics

Senior Data Scientist

Senior Data Scientist / Staff Data Scientist

Senior Data Scientist

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.

Navigating Data Science Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Data science has taken centre stage in the modern workplace. Organisations rely on data-driven insights to shape everything from product innovation and customer experience to operational efficiency and strategic planning. As a result, there is a growing need for skilled data scientists who can analyse large volumes of data, build predictive models, communicate findings effectively, and collaborate cross-functionally. If you are looking to accelerate your data science career—or even land your first role—attending data science career fairs can be a game-changer. Unlike traditional online applications, face-to-face interactions let you showcase your personality, passion, and communication skills in addition to your technical expertise. However, to stand out in a busy environment, you need a clear strategy: from polishing your personal pitch and asking thoughtful questions to following up with a memorable message. In this article, we’ll guide you through every step of making a strong impression at data science career fairs in the UK and beyond.

Common Pitfalls Data Science Job Seekers Face and How to Avoid Them

Data science has become a linchpin for decision-making and innovation across countless industries, from finance and healthcare to tech and retail. The demand for data scientists in the UK continues to climb, with businesses seeking professionals who can interpret complex datasets, build predictive models, and communicate actionable insights. Despite this high demand, the job market can be extremely competitive—and many applicants unknowingly fall into avoidable traps. Whether you’re an aspiring data scientist fresh out of university, a professional transitioning from a quantitative role, or a seasoned analyst looking to expand your skill set, it’s crucial to navigate your job search effectively. In this article, we explore the most common pitfalls data science job seekers face and provide pragmatic advice to help you stand out. By refining your CV, portfolio, interview strategies, and communication skills, you can significantly increase your chances of landing a rewarding data science role. If you’re looking for your next data science job in the UK, don’t forget to explore the listings at Data Science Jobs. Read on to discover how to avoid critical mistakes and position yourself for success.