Founding Data Scientist / Machine Learning Scientist

Fully remote role - Odd trip to London office

Subriction - Service based business

We''re working with an exciting business that is building its data science capability in-house for the first time, and they''re looking for a Founding Data Scientist to shape the function from the ground up.

This is a genuinely hands-on role where you''ll have ownership of the full data science lifecycle - from defining the modelling approach and building predictive models through to creating scalable, repeatable and production-ready solutions.

The initial focus will be on customer churn and complaint propensity, alongside forecasting and other predictive modelling opportunities. You''ll be responsible for building the models, documenting the methodology and establishing the overall approach that can be embedded and scaled across the business.

We''re particularly interested in Data Scientists who have built churn propensity models before, ideally within a subscription-based or service-led business where customer retention is a key commercial challenge.

You''ll need to be comfortable working independently and owning the end-to-end process without relying heavily on Data Engineering or a separate ML Engineering function. This means being able to take models from concept through to productionisation and build approaches that are scalable, repeatable and robust.

• Strong commercial Data Science / Machine Learning experience
• Proven experience building customer churn / propensity models
• Strong Python and SQL
• Experience taking ML models into production
• Ability to design and document modelling approaches from scratch
• Strong understanding of forecasting and predictive analytics
• Experience working with subscription, recurring revenue or field/service-based businesses is highly desirable
• Microsoft technology stack experience
• Experience using LLMs to analyse classified/unstructured data would be a bonus

This is a rare opportunity to join at the beginning of the journey and define how Data Science is done within the business, rather than simply inheriting an existing framework.

If you''ve built churn models before and want genuine ownership, autonomy and the opportunity to build something from the ground up, we''d love to hear from you.

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