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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist / Machine Learning Engineer - **Company:** Harnham - **Location:** London, UK - **Experience:** Expert - **Salary:** £156,000.0 - £208,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Microsoft Azure, Python (Programming Language), Machine Learning, NumPy, Pandas, Scikit Learn, Machine Learning Operations, Unsupervised Learning - **Published:** September 8, 2026 - **Apply:** https://www.collegerecruiter.com/job/2840573295-senior-data-scientist--machine-learning-engineer ## About the Role 3-5+ years' experience applying classical ML in commercial settings Excellent Python coding skills (production-grade, using libraries like Pandas, NumPy, scikit-learn) Strong understanding of supervised and unsupervised learning methods (regression, classification, clustering, tree-based models, etc.) Comfortable working across the full ML lifecycle Previous exposure to ambiguous or evolving problem spaces, ideally within consulting or client-facing environments * Experience with AWS / Azure and SageMaker Clear and confident communicator, able to contribute to client conversations and work collaboratively with delivery teams Degree from a top university in a quantitative discipline (Master's preferred) Based in London and able to attend the client site 2 x per week. Nice-to-Haves: Experience with geospatial modelling, time series forecasting, or operational optimisation, * 3-5+ years' experience applying classical ML in commercial settings * Excellent Python coding skills (production-grade, using libraries like Pandas, NumPy, scikit-learn) * Strong understanding of supervised and unsupervised learning methods (regression, classification, clustering, tree-based models, etc.) * Comfortable working across the full ML lifecycle * Previous exposure to ambiguous or evolving problem spaces, ideally within consulting or client-facing environments * Experience with AWS / Azure and SageMaker * Clear and confident communicator, able to contribute to client conversations and work collaboratively with delivery teams * Degree from a top university in a quantitative discipline (Master's preferred) * Based in London and able to attend the client site 2 x per week. Nice-to-Haves: * Experience with geospatial modelling, time series forecasting, or operational optimisation * DBT ## Description We're working with a specialist consultancy delivering high-impact machine learning solutions to private equity-backed businesses. They are looking for an experienced Data Scientist or ML Engineer to support a live project, applying classical machine learning to solve tangible, high-value problems. You will be joining a small, collaborative team of engineers and data scientists on-site 2 days per week in Central London. The work focuses on traditional ML use cases, such as: Optimisation modelling to improve manufacturing throughput, We're working with a specialist consultancy delivering high-impact machine learning solutions to private equity-backed businesses. They are looking for an experienced Data Scientist or ML Engineer to support a live project, applying classical machine learning to solve tangible, high-value problems. You will be joining a small, collaborative team of engineers and data scientists on-site 2 days per week in Central London. The work focuses on traditional ML use cases, such as: * Optimisation modelling to improve manufacturing throughput * Predictive modelling to anticipate and reduce asset downtime * Customer churn prediction and mitigation * Next-best-action modelling for sales agents * Geospatial modelling to inform store and asset placement decisions ## Related Videos - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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