At a Glance
- Tasks: Lead a team of data scientists to optimise payment solutions using machine learning.
- Company: Join Checkout.com, powering payments for global giants like eBay and Spotify.
- Benefits: Flexible hybrid working model, career growth opportunities, and a supportive team culture.
- Other info: Embrace a diverse environment where your growth and success are prioritised.
- Why this job: Make a real impact on millions of online shoppers while shaping the future of fintech.
- Qualifications: 2+ years managing data science teams and 5+ years as a Data Scientist.
The predicted salary is between 75600 - 92400 £ per year.
Company Description
We’re Checkout. com.
You might not know our name, but companies like e Bay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day.
We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers.
Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes.
Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.
If you want to do career-defining work, you’ve come to the right place.
We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact.
With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started.
The role
As a Data Science Manager in the Payments Performance pillar you will lead a team of smart and ambitious data scientists that drive the success of our machine learning solution for payment optimization.
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‑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.
- Strong background as a Data Scientist (5+ years of proven experience)
- 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 trade‑offs.
- 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.
- Excellent communication skills, ability to simplify machine learning concepts and data analyses for broad audiences.
- Experience dealing with data from complex domains (Fin Tech, Fraud Detection or Payments Processing are a significant plus)
- A Ph D or MS in a quantitative field (e. g., Statistics, Operations Research, Economics, Computer Science, Engineering) is considered a plus.
- Additional Information
- 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 one meaningful challenges, and be recognized for the impact you deliver.
It’s a place where ambition get 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 Linked In and Instagram
Data Science Manager Technology Data Science London employer: Checkout
Checkout.com is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation and strategic thinking are highly valued. Located in a vibrant city, employees benefit from a supportive environment that encourages professional growth through continuous learning opportunities and cross-functional collaboration. With a focus on impactful initiatives, team members are empowered to make meaningful contributions that drive the company's success.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager Technology Data Science London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Checkout!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Science Manager Technology Data Science London at Checkout.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Checkout.
✨Apply Directly through Our Website
When you find a suitable opening like Data Science Manager Technology Data Science London at Checkout, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Science Manager Technology Data Science London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Checkout, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Checkout. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Checkout
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Checkout!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
