Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to tackle real-world machine learning challenges in a hybrid role.
- Company: Work with a leading consultancy focused on impactful AI solutions for private equity businesses.
- Benefits: Enjoy a competitive daily rate, hybrid work model, and collaborative environment.
- Why this job: Make a difference by solving high-value problems while growing your skills in a supportive team.
- Qualifications: 3-5 years of ML experience, strong Python skills, and a degree in a quantitative field required.
- Other info: Interviews are happening this week; start ASAP!
The predicted salary is between 43200 - 57600 £ per year.
Senior Data Scientist / Machine Learning Engineer
Senior Data Scientist / Machine Learning Engineer
Get AI-powered advice on this job and more exclusive features.
This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from Harnham
Senior Consultant – AI, Machine Learning and Data Science
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 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
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 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
Desired Skills and Experience
Predictive Modelling, Python Machine Learning, Full ML Lifecycle
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Contract
Job function
-
Job function
Information Technology
-
Industries
Technology, Information and Internet
Referrals increase your chances of interviewing at Harnham by 2x
Sign in to set job alerts for “Senior Data Scientist” roles.
London, England, United Kingdom 7 hours ago
Senior Data Scientist – Product Insights
London, England, United Kingdom 3 weeks ago
London, England, United Kingdom 1 month ago
Machine Learning Scientists and Engineers: AI for Quantum
London, England, United Kingdom 6 days ago
London, England, United Kingdom 3 weeks ago
London, England, United Kingdom 4 days ago
Research Scientist (Quantum Chemistry and Machine Learning), London
London, England, United Kingdom 5 days ago
Sr Data Science Manager, Professional Services
London, England, United Kingdom 1 week ago
London, England, United Kingdom 1 week ago
Senior Data Science Manager, Professional Services
Greater London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 1 day ago
Senior Marketing Data Scientist – Strategic Growth Partner
London, England, United Kingdom 2 weeks ago
City Of London, England, United Kingdom 4 days ago
London, England, United Kingdom 5 days ago
Data Science Manager, Verification & Premium Support
London, England, United Kingdom 7 hours ago
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 1 week ago
London, England, United Kingdom 1 week ago
London, England, United Kingdom 3 days ago
London, England, United Kingdom 1 month ago
Senior Data and Business Analyst – Workforce Data (Ref: 5174)
London, England, United Kingdom 2 weeks ago
London, England, United Kingdom 3 weeks ago
Quantitative Researcher (Machine Learning)
Chigwell, England, United Kingdom 1 week ago
Quantitative Researcher (Machine Learning)
London, England, United Kingdom 2 months ago
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr
Senior Data Scientist / Machine Learning Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist / Machine Learning Engineer
✨Tip Number 1
Brush up on your Python skills, especially with libraries like Pandas, NumPy, and scikit-learn. Being able to demonstrate your coding proficiency in these areas during discussions can set you apart from other candidates.
✨Tip Number 2
Familiarise yourself with the full machine learning lifecycle. Be prepared to discuss your experiences in each phase, as this role requires a comprehensive understanding of how to take a project from conception to deployment.
✨Tip Number 3
Since the role involves client-facing interactions, practice articulating complex ML concepts in simple terms. This will help you communicate effectively with clients and showcase your ability to collaborate within a team.
✨Tip Number 4
If you have experience with AWS or Azure, be ready to discuss specific projects where you've used these platforms. Highlighting your practical knowledge can demonstrate your readiness for the technical demands of the job.
We think you need these skills to ace Senior Data Scientist / Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in classical machine learning and Python coding. Include specific projects where you've applied supervised and unsupervised learning methods, as well as any relevant tools like AWS or Azure.
Craft a Strong Cover Letter: In your cover letter, emphasise your ability to work collaboratively in a team and your experience in client-facing environments. Mention how your skills align with the company's focus on high-impact machine learning solutions.
Showcase Relevant Projects: Include a section in your application that details specific projects you've worked on that relate to the job description. Highlight your contributions to optimisation modelling, predictive modelling, or any geospatial modelling experience.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during interviews. Prepare examples of how you've tackled ambiguous problems and your approach to the full ML lifecycle, as these are key aspects of the role.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and machine learning libraries like Pandas, NumPy, and scikit-learn. Bring examples of projects where you've applied classical ML techniques, as this will demonstrate your hands-on expertise.
✨Understand the Business Context
Research the consultancy's focus on private equity-backed businesses and their specific challenges. Be ready to discuss how your skills can help solve real-world problems, such as customer churn prediction or optimisation modelling.
✨Communicate Clearly
As a clear and confident communicator, practice explaining complex concepts in simple terms. This is crucial when discussing your work with clients or collaborating with team members, especially in a consulting environment.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to navigate ambiguous problem spaces. Think of examples from your past experiences where you successfully tackled evolving challenges, and be ready to share your thought process.
