Senior Data Scientist / Machine Learning Engineer

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

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