At a Glance
- Tasks: Lead analytics for innovative financial products and drive data-driven decision-making.
- Company: Join Checkout.com, a key player in fintech powering major brands like eBay and Spotify.
- Benefits: Flexible hybrid work model, real ownership, and opportunities for personal growth.
- Other info: Dynamic team culture that values diversity and supports your career journey.
- Why this job: Make a real impact in shaping the future of digital finance with cutting-edge analytics.
- Qualifications: Experience in analytics leadership and product performance evaluation.
The predicted salary is between 59400 - 72600 £ 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.
As an Analytics Manager for Financial Experiences, you will lead analytics for one of Checkout. com’s strategically important product areas.
Financial Experiences (Fe X) exists to give customers modern solutions to control and manage their money.
The product pillar spans products and capabilities across Checkout Business Account and balances, acceleration, FX, financial reporting and invoicing, pricing and billing, bank payouts, and client settlements.
You will be a co-owner of product success in the pillar: shaping how we measure performance, building the data foundations and self-serve products required to support decision-making, and generating insights that influence roadmap priorities and product outcomes.
What you will do
- You will manage & lead a small team of analytics engineers and product analysts
- Own the analytics roadmap for Fe X, ensuring we are focused on the highest-value opportunities across product measurement, merchant insight, pricing, billing and funds management
- Define the measurement frameworks, north-star metrics, supporting KPIs, and decision mechanisms that help Fe X teams understand whether products are creating value for merchants and for Checkout. com.
- Partner with Product and Engineering leaders to ensure products are correctly instrumented, the right data is captured, and analytics output is trustworthy, scalable, and actionable.
- Deliver self-serve data products, dashboards, and analyses that help teams monitor performance, identify product improvement opportunities, and make better trade-offs faster.
- Increase the data maturity of the pillar by embedding rigorous, data-driven decision-making into discovery, prioritisation, launch measurement, and ongoing product development.
- What we’re looking for
- Experience leading analytics, product analytics, and/or analytics engineering in a product-led environment.
- Demonstrable experience in building descriptive measurement and delivering insights to evaluate product performance and validate impact.
- Experience delivering data products, self-serve analytics, and data models that support decision-making at scale.
- Strong analytical problem-solving skills, with the ability to turn ambiguous business and product questions into clear, structured, data-informed recommendations.
- Proven ability to work cross-functionally with senior stakeholders, align priorities, and scope analytical delivery in complex environments.
- Technical foundation in analytics engineering, ideally building data pipelines with DBT, working with cloud data warehouses, scheduling/orchestration of data pipelines
- Ideally, experience in payments, fintech, financial products, pricing, billing, treasury, or adjacent financial domains.
- 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 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 Linked In and Instagram.
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Analytics Manager, Financial Experiences London employer: Checkout
Checkout.com is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for professionals looking to make a significant impact in the financial technology sector. With a strong focus on employee growth and development, team members are encouraged to expand their skills and take on new challenges, all while enjoying the vibrant atmosphere of London. The company's commitment to regulatory excellence and strategic expansion offers unique opportunities for those passionate about shaping the future of global finance.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Manager, Financial Experiences London
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We think you need these skills to ace Analytics Manager, Financial Experiences 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!
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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!
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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.
