Data Scientist

Checkout.com is hiring a Data Scientist in London, United Kingdom. Level rates it ; you can apply on Checkout.com.

Level's read on this job

Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
Tools and skills the posting cites include Databricks, Python and AI evaluation.
Level classifies it as a senior role.
Level lists 171 other open roles at Checkout.com.

AI in this role

Develop machine learning models and estimators to boost payment performance and acceptance rates.

DatabricksPython

ai-evaluationmachine-learningfeature-engineeringstatistical-modelingexperiment-designbayesian-statistics

Company Description

We’re Checkout.com. You might not know our name, but companies like eBay, 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.

About the Role

Checkout.com is looking for a Data Scientist to join our ambitious team, focused on discovering, designing, and experimenting with new estimators, models and features to boost payment performance across our portfolio of merchants. You will work closely with Data Scientists, Product and Engineering to enhance our core offering, protect customer lifetime value through network intelligence, and ensure safe model launches through robust observability.

Key Responsibilities

Contribute to the research and development of new ML models and estimators to boost core Acceptance Rate performance.
Design and implement experiments to produce actionable insights, focusing on managing time-based data leakage and ensuring robust model evaluation.
Collaborate with other Data Scientists and engineers to productionise ML features, models and evolve our evaluation and monitoring frameworks.
Write high-quality, interpretable Python code for feature engineering and model training, contributing directly to our core products.
Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical and non-technical audiences.

About You

3+ years of experience developing machine learning models to solve business problems.
Strong understanding of supervised ML algorithms, tuning, and performance evaluation.
Experience with a range of feature engineering techniques (e.g. target encoding).
Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation.
Experience in writing clean, production-grade Python code for both model training and inference.
Excited to leverage LLMs for coding support and process optimisation to maximise personal and team productivity.

Nice to have

Experience with advanced data transformation techniques (e.g., lambda functions).
Familiarity with, or hands-on experience in, recommender systems, contextual bandits, or network intelligence applications.
Experience in fintech, payments, or building cross-disciplinary relationships for advice and guidance.
Familiarity with the unix shell, Databricks, Docker, and common cloud platforms (GCP/AWS).

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 LinkedIn and Instagram

How we rate this

Data Scientist at Checkout.com rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Scientist is an open job at Checkout.com.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in London.
The job was posted on July 14, 2026.
Seniority: senior.
Applications are handled by Checkout.com. Apply on Checkout.com

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI EvaluationMachine learningFeature EngineeringStatistical ModelingExperiment DesignBayesian StatisticsDatabricksPython

Also common in data scientist jobs at this level

SQL Generative AI Spark PyTorch Deep learning NLP

Pay

Typical data scientist job: $167k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

How do you decide that one model's output is better than another's for a given task?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where feature engineering was part of your work. What did you do?
Tell me about a project where statistical modeling was part of your work. What did you do?
Tell me about a project where experiment design was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Evaluation, Machine learning, Feature Engineering, Statistical Modeling, and Experiment Design. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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