Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and manage ML platforms to enhance pricing workflows and enable rapid model deployment.
- Company: Leading consulting firm in London with a focus on innovation.
- Benefits: Competitive contract pay and the chance to work with top professionals.
- Why this job: Join a dynamic team and make a real impact on pricing technology.
- Qualifications: Background in Statistics or Data Science, strong ML experience, and Python proficiency.
- Other info: Collaborative environment with opportunities to work across various teams.
The predicted salary is between 48000 - 72000 £ per year.
A leading consulting firm in London is seeking a Machine Learning Engineer to enhance and scale their pricing technology. In this position, you will design and manage ML platforms that improve pricing workflows, enabling rapid model deployment.
The ideal candidate will possess a background in Statistics or Data Science, exhibit strong experience in ML model lifecycle management, and demonstrate proficiency in Python.
This contract role offers the opportunity to work collaboratively with Data Science, Actuarial, and Product teams.
Pricing ML Platform Engineer — Contract in London employer: G MASS Consulting
Contact Detail:
G MASS Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Pricing ML Platform Engineer — Contract in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in ML or pricing tech. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those related to pricing workflows. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and ML model lifecycle management knowledge. We recommend practising common interview questions and even doing mock interviews with friends to build confidence.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Pricing ML Platform Engineer — Contract in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in ML model lifecycle management and Python. We want to see how your background in Statistics or Data Science aligns with the role, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about enhancing pricing technology and how your skills can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Collaboration Skills: Since this role involves working with various teams like Data Science and Actuarial, make sure to mention any past experiences where you’ve successfully collaborated. We value teamwork, so let us know how you can fit into our dynamic environment!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at G MASS Consulting
✨Know Your ML Models Inside Out
Make sure you can discuss the entire lifecycle of machine learning models. Be prepared to explain how you've managed model deployment and scaling in previous roles, as this will show your hands-on experience and understanding of the process.
✨Brush Up on Python Skills
Since proficiency in Python is key for this role, review your coding skills before the interview. Be ready to solve a coding challenge or discuss your past projects where you used Python for ML tasks.
✨Understand Pricing Workflows
Familiarise yourself with pricing technology and workflows. Research how machine learning can enhance pricing strategies, and be prepared to share your insights or ideas on how to improve these processes.
✨Collaborate and Communicate
This role involves working with various teams, so highlight your collaborative experiences. Think of examples where you successfully worked with Data Science, Actuarial, or Product teams, and be ready to discuss how you can contribute to a team environment.
