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- Tasks: Join a team to test and improve optimisation algorithms for energy systems.
- Company: Work with a global organisation leading in Balancing Transformation programmes.
- Benefits: Enjoy a collaborative Agile environment and the chance to work on cutting-edge cloud-native platforms.
- Why this job: Make a real impact in energy systems while developing your skills in a dynamic team.
- Qualifications: Degree in Engineering, Mathematics, Physics or Operations Research; coding skills in Python required.
- Other info: Ideal for those passionate about optimisation methods and energy systems.
The predicted salary is between 48000 - 72000 £ per year.
Our client, a global organisation, is looking for an Optimisation SME in their Balancing Transformation programme. You will be responsible for delivering quality algorithm testing to production new tools to help balance the system. You will be working in a team of experts, engaging with the IT and the business in an Agile delivery environment, to deploy solutions in a state-of-the-art cloud-native IT platform.
Specific responsibilities include (but are not limited to):
- Work with the project team and the customer team on the Dispatch algorithm as part of Balancing Transformation programs.
- Test control and optimisation algorithms.
- Improve and maintain existing algorithms and control processes.
- Collaborate with internal teams for the implementation of new capabilities in our IT platform.
- Support in Quality Assurance of Modern Optimisation Algorithm.
- Coordinate with different functional teams and Business.
We are looking for someone who:
- Has an operations research background – excellent understanding of optimisation methods and control algorithms, and experience in applying them to real-world problems.
- Has solid coding skills in Python.
- Has an analytical mindset, attention to detail, and is comfortable with collecting and interpreting data to support end-to-end solution design.
- Has a keen interest in energy systems.
- Experience solving the optimisation problem using various techniques.
- Develop custom data models and algorithms to apply to data sets.
- Strong understanding of mathematical programming solvers available for your LP, QP and MIP (MILP, MIQP, and MIQCP) problems.
- Understanding of data collection, preprocessing and analysis.
- Python, Gurobi Optimizer.
- Has a degree in Engineering, Mathematics, Physics or Operations Research.
- Understanding of electricity markets and power system operations (including related economic dispatch/unit-commitment type of problems).
- Experience with delivering IT solutions in cloud-native environments.
- MSc or PhD in a related subject.
If you are interested and have the relevant experience, please apply promptly and we will contact you to discuss further.
Senior Optimization Engineer employer: Queen Square Recruitment
Contact Detail:
Queen Square Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Optimization Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in optimisation algorithms and cloud-native IT platforms. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the energy systems sector, especially those who work with optimisation methods. Engaging in discussions or attending relevant webinars can provide insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss specific projects where you've applied optimisation techniques, particularly in real-world scenarios. Being able to articulate your experience will set you apart from other candidates.
✨Tip Number 4
Showcase your coding skills in Python by working on personal projects or contributing to open-source initiatives. This practical experience can be a great talking point during interviews and demonstrates your hands-on abilities.
We think you need these skills to ace Senior Optimization Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with optimisation methods, control algorithms, and any relevant projects. Emphasise your coding skills in Python and any specific tools like Gurobi Optimizer that you've used.
Craft a Strong Cover Letter: In your cover letter, express your passion for energy systems and how your background in operations research aligns with the role. Mention specific examples of how you've solved optimisation problems in previous roles.
Showcase Relevant Projects: If you have worked on projects related to algorithm testing or cloud-native IT solutions, be sure to include these in your application. Detail your contributions and the outcomes to demonstrate your impact.
Highlight Analytical Skills: Since the role requires an analytical mindset, provide examples of how you've collected and interpreted data to support solution design. This could be through coursework, previous jobs, or personal projects.
How to prepare for a job interview at Queen Square Recruitment
✨Showcase Your Technical Skills
Make sure to highlight your coding skills in Python and your experience with optimisation methods. Be prepared to discuss specific algorithms you've worked on and how you've applied them to real-world problems.
✨Demonstrate Your Analytical Mindset
Prepare examples that showcase your attention to detail and your ability to collect and interpret data. Discuss how you've used data to support solution design in previous projects.
✨Understand the Industry Context
Familiarise yourself with electricity markets and power system operations. Being able to discuss these topics will show your keen interest in energy systems and your understanding of the challenges faced in this field.
✨Emphasise Collaboration Experience
Since the role involves working in an Agile environment, be ready to talk about your experience collaborating with cross-functional teams. Highlight any successful projects where teamwork was key to delivering IT solutions.
