Product Data Scientist: Onboarding Optimization & Automation

Checkout.com; Greater London; Hybrid; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Checkout.com is seeking a Product Data Scientist to join a cross-functional team focused on Platforms and SMB onboarding optimization, data-driven automation, and product measurement.

You will build experiments, log and model data to generate insights, design PoC ML models, and present findings to Product Managers and engineers. This highly visible analytics function collaborates with Senior Data Scientists and Analytics Engineers to influence product strategy.

Qualifications

• Experience in data science or product analytics in a high-growth tech environment.
• Strong SQL and Python skills for data querying and analysis.
• Foundational ML concepts (statistics, clustering, NLP) and how to apply them to data tasks.
• Analytical mindset with ability to translate operational problems into data-informed solutions.
• Clear and concise communication of data insights to non-technical stakeholders.

Responsibilities

• Build experiments and analysis frameworks to measure operational efficiency and ROI of onboarding initiatives.
• Collaborate with Data Analytics Engineers and Software Engineers to ensure proper data logging and modeling of key signals.
• Design and run PoC machine learning models and heuristics to evaluate onboarding automation feasibility.
• Translate insights into actionable recommendations for Product Managers and Operations teams.

Skills

Experience in data science/product-qa

Analytical mindset

Communication skills

Foundational ML knowledge

Tools

SQL

Python

ML basics

Job description

Checkout.com is seeking a Product Data Scientist to join a cross-functional team focused on Platforms and SMB onboarding optimization, data-driven automation, and product measurement.

You will build experiments, log and model data to generate insights, design PoC ML models, and present findings to Product Managers and engineers. This highly visible analytics function collaborates with Senior Data Scientists and Analytics Engineers to influence product strategy.