Senior Data Scientist / Machine Learning Engineer

ZipRecruiter; London; Hybrid; GBP 125,000 - 150,000; Full time

Job summary

An innovative consultancy is seeking a Contract Senior Data Scientist / ML Engineer to deliver impactful machine learning solutions. This role involves applying classical ML techniques to optimize manufacturing processes, predict asset downtime, and enhance customer interactions. You will collaborate with a dedicated team in a hybrid work environment, contributing to client projects that drive significant business value. If you thrive in dynamic settings and have a passion for solving complex problems, this opportunity is perfect for you.

Qualifications

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

Responsibilities

• Support live projects applying classical ML to solve high-value problems.
• Work collaboratively with a small team of engineers and data scientists.

Skills

Python

Classical Machine Learning

Data Science

AWS

Azure

Communication Skills

Education

Master's Degree in Quantitative Discipline

Tools

Pandas

NumPy

scikit-learn

SageMaker

DBT

Job description

Job Description

Contract Senior Data Scientist / ML Engineer£600-800/day | Outside IR35 | Hybrid (Central London, 2 days/week)

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

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)
• 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.