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- Tasks: Join a team to deploy machine learning models in live pricing systems using Python.
- Company: Dynamic company at the forefront of machine learning and analytics.
- Benefits: Up to £40,000 salary, hybrid working, and career growth opportunities.
- Why this job: Make a real impact on business performance with cutting-edge machine learning technology.
- Qualifications: Strong Python skills and a passion for machine learning systems.
- Other info: Collaborative environment with experienced engineers to support your growth.
The predicted salary is between 28800 - 48000 £ per year.
This is an exciting opportunity to build a career in production machine learning within a large scale pricing and analytics environment. You will join a growing Machine Learning Operations team at the heart of a major transformation programme. The focus is on modernising how pricing models are built, tested and deployed into live systems. This role is ideal if you enjoy Python, problem solving and want to understand how machine learning works in real business settings rather than just notebooks.
This is not a research focused role and it is not purely infrastructure. The impact happens in the middle, where models become reliable, scalable and ready for customers.
What you will be doing:
- Working on Python based rating and machine learning deployments used in live pricing systems
- Supporting testing and analysis to ensure changes are accurate, controlled and high quality
- Building and improving tools, frameworks and APIs that help teams deploy models with confidence
- Collaborating with engineers, analysts and stakeholders to turn ideas into working solutions
- Contributing to clear and well-structured technical documentation
- Developing an understanding of how machine learning impacts customer pricing and business performance
What you will bring:
- A genuine interest in machine learning systems and how models move into production
- Strong Python fundamentals and a desire to grow your engineering capability
- A degree in a mathematical or technical subject or equivalent practical experience
- Logical thinking and a structured approach to problem solving
- Curiosity, initiative and a willingness to learn
- Clear communication skills and comfort working as part of a collaborative team
You will work on real systems that matter, not isolated exercises. You will be supported by experienced engineers, exposed to modern tooling, and given the space to build confidence in production machine learning and ML Operations. This role is designed to set strong foundations for long term technical growth.
Right to work: You must be eligible and authorised to work in the United Kingdom.
Junior ML Operations Engineer (Python) in Manchester employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior ML Operations Engineer (Python) in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. 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 projects, especially those related to machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML Ops questions and practical coding challenges. Practice explaining your thought process clearly, as communication is key in collaborative environments.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Junior ML Operations Engineer (Python) in Manchester
Some tips for your application 🫡
Show Your Python Passion: Make sure to highlight your Python skills in your application. We want to see how you've used Python in real-world scenarios, especially in machine learning contexts. Share any projects or experiences that showcase your coding prowess!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured documents that are easy to read. Avoid jargon unless it's necessary, and make sure your enthusiasm for the role shines through!
Demonstrate Your Problem-Solving Skills: We love candidates who can think logically and tackle problems head-on. In your application, include examples of challenges you've faced and how you approached them. This will show us your structured thinking and initiative!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved!
How to prepare for a job interview at Datatech Analytics
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in detail, especially in relation to machine learning deployments. Practise coding challenges or projects that showcase your ability to solve problems using Python.
✨Understand Machine Learning in Practice
Since this role focuses on how machine learning models are deployed in real business settings, take some time to understand the practical applications of ML. Be prepared to discuss how you've seen or used ML in previous projects, and think about how it impacts customer pricing and business performance.
✨Prepare for Collaboration Questions
This position requires working closely with engineers, analysts, and stakeholders. Think of examples from your past experiences where you successfully collaborated with others. Highlight your communication skills and how you contributed to turning ideas into working solutions.
✨Show Your Curiosity and Willingness to Learn
Employers love candidates who are eager to learn and grow. Be ready to share instances where you've taken the initiative to learn something new, whether it's a tool, framework, or concept related to ML operations. This will demonstrate your passion for the field and your commitment to personal development.
