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- Tasks: Join a dynamic team to tackle real-world problems using machine learning.
- Company: A leading consultancy focused on impactful ML solutions for private equity-backed businesses.
- Benefits: Enjoy a competitive daily rate, hybrid work model, and collaborative environment.
- Why this job: Make a difference with your skills while working on exciting projects in Central London.
- Qualifications: 3-5+ years in ML, strong Python skills, and a degree in a quantitative field required.
- Other info: Interviews happening this week; start ASAP!
The predicted salary is between 120000 - 168000 £ per year.
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.
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
Make sure to brush up on your Python skills, especially with libraries like Pandas and NumPy. Being able to demonstrate your coding proficiency during discussions can set you apart from other candidates.
✨Tip Number 2
Familiarise yourself with the specific machine learning techniques mentioned in the job description, such as optimisation modelling and predictive modelling. Prepare examples of how you've applied these methods in past projects to showcase your experience.
✨Tip Number 3
Since this role involves client-facing interactions, practice articulating complex ML concepts in simple terms. Being a clear communicator will help you connect better with potential clients and team members.
✨Tip Number 4
Research the company and its recent projects or case studies. Understanding their approach to machine learning solutions will allow you to tailor your conversations and show genuine interest in their work.
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. Emphasise your work with libraries like Pandas, NumPy, and scikit-learn, as well as any relevant projects that demonstrate your skills in optimisation modelling and predictive modelling.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in this specific role and how your background aligns with the company's needs. Mention your experience in client-facing environments and your ability to communicate complex concepts clearly.
Showcase Relevant Projects: If you have worked on projects related to customer churn prediction, geospatial modelling, or operational optimisation, be sure to include these in your application. Provide brief descriptions of the challenges faced and the solutions you implemented.
Highlight Your Educational Background: Since a degree from a top university in a quantitative discipline is preferred, make sure to mention your educational qualifications prominently. If you have a Master's degree, highlight it as it adds value to your application.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and the libraries mentioned in the job description, such as Pandas and scikit-learn. You might be asked to solve a coding problem or explain your approach to a specific machine learning task, so brush up on your technical knowledge.
✨Demonstrate Problem-Solving Abilities
Since the role involves tackling ambiguous problems, think of examples from your past work where you successfully navigated uncertainty. Be ready to explain your thought process and how you approached these challenges, particularly in a consulting environment.
✨Communicate Clearly and Confidently
As a Senior Data Scientist or ML Engineer, you'll need to engage with clients and team members effectively. Practice articulating complex concepts in simple terms, and prepare to discuss how you've collaborated with others in previous roles.
✨Familiarise Yourself with the Company’s Focus Areas
Research the consultancy's projects and the specific machine learning applications they are working on, such as predictive modelling and optimisation. This will help you tailor your responses and demonstrate your genuine interest in their work during the interview.
