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# Senior Product Data Scientist

- **Company:** Checkout.com
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Internship / Graduate position
- **Skills:** BASIC (Programming Language), Cluster Analysis, SQL Databases, Scripting, Large Language Models, Data Analytics, Machine Learning Operations, Text Analysis
- **Published:** June 29, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=0bddb7558ecb2fd0

## About the Role

Do you have experience in SQL?, * Technical foundations: Excellent data interrogation skills with SQL and the ability to comfortably write, read, and iterate through Python scripts to run data science analyses.

 * Foundational ML knowledge: A good understanding of foundational data science concepts (e.g., statistics, clustering, basic NLP workflows). You do not need experience deploying ML models to production, but you should understand how to apply them to data tasks.
 * Analytical Mindset: A strong analytical mind with a demonstrable ability to take operational problems and convert them into structured, data-informed solutions.
 * Communication: Clear and precise communicator, able to explain data insights and analytical logic to non-technical stakeholders (Product Managers and Operations teams).

Experience: Prior experience or a strong internship background in product analytics, risk/compliance data, or a high-growth tech environment is a plus.

## Description

* Efficiency & Product Measurement: Build frameworks to measure the operational efficiency and ROI of new software releases and internal tooling updates within Merchant Care.
 * Data Partnerships: Work closely with Data Analytics Engineers and Software Engineers to ensure we log and model the right data to produce high-integrity business insights.
 * Data-driven automations and solutions:
 + Run historical data simulations to analyze how changes in our deterministic AML rule thresholds affect review backlogs, and suggest optimal logic updates to our SQL-based alerts.
 + Support the development and testing of a Level 1 (L1) automated discounting agent for transaction monitoring alerts, building on existing team frameworks.
 * Text Analytics & Insights: Use clustering techniques and LLM-based summary extraction on merchant ticket conversations to identify recurring user friction points and help product teams map future features.


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