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# Commercial Data Scientist

- **Company:** Checkout.com
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Machine Learning, SQL Databases, Technical Data Management Systems
- **Published:** July 30, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=f7ba5c02899d6d5b

## About the Role

* Strong proficiency in SQL and Python with experience building and maintaining predictive models.
 * Prior experience as a Data Scientist in a commercial set-up, delivering predictive models/timeseries models to aid sale/demand forecasting
 * Experience working with cross-functional partners (Finance, Product, and Ops) to deliver actionable insights.
 * Ability to explain technical data concepts to non-technical stakeholders clearly and concisely.
 * Prior experience in a commercial, fintech, or high-growth environment is preferred.

## Description

As a Commercial Data Scientist at Checkout.com, you will be the primary operator of our Growth Prediction Engine. Your focus will be to maintain and evolve the models that underpin our commercial strategy, working closely with Strategic Finance and Revenue Operations.

The growth forecasting framework is an established roadmap. You will own the execution of these models while working in a shared-delivery model where tasks are distributed across the wider Data Science team.

How You'll Make an Impact

 * Advance our ML-Driven Forecasting: Own, maintain, and continuously enhance our ML-driven revenue growth models. You will be responsible for pushing these models to the next level and proactively expanding their use cases beyond the commercial domain.
 * Drive Strategic Financial Modeling: Partner with Strategic Finance to build robust projections and simulations based on our forecast model outputs, approaching this with the mindset of building scalable, automated tools rather than just ad-hoc reports.
 * Unlock Commercial Data Science Applications: Work closely with the Revenue Operations team to identify, unlock, and deploy other high-impact commercial data science applications that increase the quality and utilization of our data.
 * Champion Best Practices: Lead by example within your team and the broader data community by applying best practices in analytics and machine learning, from data collection to deployment and analysis.


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