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- Tasks: Build and maintain Python-based machine learning models in a collaborative team.
- Company: Join a major organisation transforming pricing and analytics with innovative technology.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Why this job: Shape the future of machine learning and make a real impact in a dynamic environment.
- Qualifications: Strong Python skills and experience in machine learning engineering required.
- Other info: Exciting career development opportunities in a leading analytics recruitment agency.
The predicted salary is between 43200 - 66000 £ per year.
Location: Manchester | Hybrid working - currently 40% on site increasing to 60% within 12 months
Salary: Up to £66,000 depending on experience
Ref: J13039
Join a major organisation investing heavily in its Pricing and Analytics transformation. This is a hands-on opportunity to shape how machine learning and pricing models are built, deployed, and scaled in a modern production environment.
You will work in a collaborative, engineering-led team focused on high quality Python modelling, automation, and robust deployment practices. The role offers genuine influence over tooling, frameworks, and standards as the function continues to grow.
Role:
- Building and maintaining Python based modelling frameworks and tooling
- Supporting the full lifecycle of machine learning and statistical models
- Enabling scalable, production ready model deployment through reusable engineering solutions
- Working closely with analytics, pricing, and wider stakeholders to ensure models are robust and well governed
- Contributing to best practice, code quality, and continuous improvement
Experience:
- Strong experience in Python modelling and machine learning engineering
- Background operating at senior analyst level or equivalent
- Experience deploying and supporting models in a commercial environment
- Exposure to GLM and or GBM models is beneficial
- Insurance or pricing modelling experience is highly desirable
- Comfortable working with Git and collaborative development practices
- Able to communicate clearly with both technical and non-technical teams
- UK right to work required. Sponsorship is not available.
Apply to learn more or message for a confidential conversation.
If you have a friend or colleague who may be interested, please refer them to us. For each successful placement, you will be eligible for our general gift or voucher scheme.
Datatech is one of the UK’s leading recruitment agencies specialising in analytics and is the host of the critically acclaimed Women in Data event. For more information, visit www.datatech.org.uk
Machine Learning Engineer (Python) in Manchester employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Python) in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning Engineers. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python modelling projects and any machine learning models you've built. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with model deployment and collaboration with teams. Practising common interview questions can help you feel more confident.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Machine Learning Engineer (Python) in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python modelling and machine learning experience. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Don’t forget to mention your experience with Git and any exposure to GLM or GBM models. We’re looking for someone who can hit the ground running, so let us know what tools you’re comfortable with!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Datatech Analytics
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially in relation to machine learning frameworks. Be prepared to discuss your experience with Python modelling and any specific projects you've worked on. Practising coding problems can also help you feel more confident.
✨Understand the Business Context
Since this role involves pricing and analytics, it’s crucial to understand how machine learning impacts these areas. Research the company’s approach to pricing models and think about how your skills can contribute to their transformation efforts. This will show your genuine interest in the role.
✨Prepare for Technical Questions
Expect questions about deploying models and working with GLM or GBM models. Brush up on your knowledge of model governance and best practices in machine learning. Being able to articulate your thought process during technical challenges will impress the interviewers.
✨Showcase Your Collaboration Skills
This role requires working closely with various stakeholders, so be ready to discuss your experience in collaborative environments. Share examples of how you've communicated complex technical concepts to non-technical teams, as this will highlight your ability to bridge gaps between different groups.
