Senior Data Scientist / Machine Learning Engineer

JR United Kingdom; London; Hybrid; GBP 125,000 - 150,000; Full time

Job summary

An innovative consultancy seeks a Senior Data Scientist or ML Engineer to tackle high-impact machine learning challenges for private equity-backed businesses. This role offers the opportunity to apply classical machine learning methods to real-world problems, such as predictive modelling and optimisation. You will collaborate with a dynamic team, working on-site in Central London two days a week. If you are passionate about data science and eager to contribute to transformative projects, this position is perfect for you. Join a forward-thinking firm and make a tangible impact in the industry!

Qualifications

• 3-5+ years of experience in applying classical ML in commercial settings.
• Strong understanding of supervised and unsupervised learning methods.

Responsibilities

• Join a collaborative team to apply classical ML for high-value business problems.
• Work on optimisation and predictive modelling to enhance operations.

Skills

Python

Machine Learning

AWS

Azure

Data Analysis

Geospatial Modelling

Predictive Modelling

Optimisation Modelling

Education

Master's in Quantitative Discipline

Bachelor's in Quantitative Discipline

Tools

Pandas

NumPy

scikit-learn

DBT

SageMaker

Job description

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Senior Data Scientist / Machine Learning Engineer, London

Contract Senior Data Scientist / ML Engineer

£600-800/day | Outside IR35 | Hybrid (Central London, 2 days/week)

We are working with a specialist consultancy delivering high-impact machine learning solutions to private equity-backed businesses. They seek an experienced Data Scientist or ML Engineer to support a live project, applying classical machine learning to solve tangible, high-value problems.

You will join 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

Must-Have Requirements:

• 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

Interviews are taking place this week. Start ASAP.

Please email your application to the provided contact.