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- Tasks: As a Senior Product Data Scientist, you'll analyze product data and drive strategy with actionable insights.
- Company: Checkout.com is a leading fintech empowering businesses in the digital economy with innovative payment solutions.
- Benefits: Enjoy a hybrid work model, amazing snacks, and a supportive community that values diversity and inclusion.
- Why this job: Join a dynamic team to influence product success and make a real impact in a fast-paced environment.
- Qualifications: Strong communication skills, experience in analytics, SQL proficiency, and a knack for solving complex problems.
- Other info: We prioritize equal opportunities and support your success with a comfortable working environment.
The predicted salary is between 43200 - 72000 £ per year.
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.
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:
- You’ll be responsible for analytics of a product domain. You’ll define, measure, and present metrics, deliver actionable insights.
- Contribute product roadmaps through data-based recommendations and continuously define high-impact areas for improvement.
- Working closely with Data Analytics Engineers and Software Engineers to make sure we collect and model the right data to produce relevant business insights.
- Foster data culture across products and technology by actively sharing insights and ideas and building positive relationships with colleagues.
- Build experiments and analysis frameworks to quantify the ROI of product development.
- Lead by example your team and the broader data community to apply best practices in analytics from data collection to analysis.
Qualifications
- Strong communicator, you’re able to explain complex technical topics to non-technical team members.
- Experience conducting experiments, building measurement frameworks, and validating the results with relevant quantitative methods.
- Strong analytical mind and demonstrable experience in converting ambiguous problems into structured and data-informed solutions.
- Excellent data interrogation skills with SQL.
- 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.
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Senior Product Data Scientist London employer: Checkout Group
Contact Detail:
Checkout Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Product Data Scientist London
✨Tip Number 1
Familiarize yourself with Checkout.com's product offerings and the fintech landscape. Understanding how our payment solutions work and the challenges businesses face in the digital economy will help you articulate your insights during discussions.
✨Tip Number 2
Showcase your experience with data-driven decision-making. Be prepared to discuss specific examples where your analytical skills led to measurable improvements in product performance or user experience.
✨Tip Number 3
Highlight your collaboration skills. Since you'll be working closely with cross-functional teams, share instances where you've successfully partnered with product managers, designers, or engineers to drive product success.
✨Tip Number 4
Demonstrate your knowledge of SQL and applied statistics. Be ready to discuss how you've used these skills in past roles to analyze data, conduct experiments, and validate results, as this is crucial for the Senior Product Data Scientist position.
We think you need these skills to ace Senior Product Data Scientist London
Some tips for your application 🫡
Understand the Company: Dive deep into Checkout.com’s mission and values. Familiarize yourself with their products and the impact they have on the digital economy. This will help you tailor your application to align with their goals.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience in analytics, product data science, and any relevant projects. Showcase your ability to convert complex problems into structured solutions, as this is crucial for the role.
Demonstrate Communication Skills: Since strong communication is key for this position, provide examples of how you've successfully explained technical concepts to non-technical stakeholders. This could be through past projects or presentations.
Showcase Your Analytical Skills: Include specific instances where you've used SQL and applied statistical methods to drive product improvements. Mention any experiments or measurement frameworks you've built to validate results.
How to prepare for a job interview at Checkout Group
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data analysis and how you've used SQL to derive insights. Highlight specific examples where your analytical mind helped solve complex problems.
✨Communicate Clearly
Since the role requires explaining technical topics to non-technical team members, practice articulating your thoughts clearly. Use simple language to describe your past projects and their impact.
✨Demonstrate Collaboration
Emphasize your experience working in cross-functional teams. Share examples of how you collaborated with product managers, designers, and engineers to drive product success.
✨Prepare for Behavioral Questions
Expect questions about how you handle ambiguity and make data-informed decisions. Prepare stories that illustrate your problem-solving process and how you’ve contributed to a positive data culture.
