At a Glance
- Tasks: Drive predictive maintenance initiatives using data science and machine learning to prevent asset failures.
- Company: Join a forward-thinking company focused on innovation and technology.
- Benefits: Competitive day rate, remote work flexibility, and potential for contract extension.
- Other info: Work in a dynamic environment with opportunities for professional growth.
- Why this job: Make a real impact by solving commercial problems with cutting-edge machine learning techniques.
- Qualifications: Experience in data science, machine learning, and stakeholder management.
The predicted salary is between 50000 - 60000 £ per year.
We are seeking a highly experienced and organised Predictive Maintenance Data Scientist to join our client. The successful candidate will own and deliver data-driven predictive maintenance initiatives, focused on identifying and preventing failures across physical assets such as infrastructure, machinery, or vehicles. As a well-rounded data scientist, you will leverage strong applied machine learning expertise, combining data science and engineering to drive business impact. Operating as a senior individual contributor, you will take a consultative approach, working closely with stakeholders to define requirements, contribute to the product roadmap, and ensure delivery against objectives, timelines, scope, and quality standards.
Key Skills:
- Full stack data scientist with both science and engineering skills to develop ML solutions and get them into production.
- Senior individual contributor, able to draw upon a wide experience of problems and solutions to technically guide more junior data scientists.
- Stakeholder management skills (defining and prioritising requirements, contributing to product roadmap, supporting adoption). Motivated as much by creating business value as by algorithmic excellence.
- Expert in applied machine learning, including the techniques currently being used in PRISM (XGBoost and SHAP).
- Experience of using machine learning to solve commercial predictive maintenance problems. Not necessarily for aircraft maintenance, could be other physical assets.
- Ideally, experience with Causal ML, since this is a direction client is considering going with PRISM.
This is a 6-month contract (possibility of extension) with a day rate, in-scope of IR35, either via a Hays approved umbrella company or via Hays PAYE. This role provides remote working access from the comforts of your own home and only requires going to our state-of-the-art office in Waterside, London 3 days per week.
Once you’ve applied, one of our friendly recruitment consultants will give you a call and talk you through the screening process. If your application is successful, you’ll be involved in a live virtual interview with one of our client’s hiring managers to get to know you better.
Predictive Maintenance Data Analyst in England employer: Hays
Our client is an exceptional employer that values innovation and collaboration, offering a dynamic work culture where data-driven insights lead to impactful solutions. With a focus on employee growth, they provide opportunities for professional development and the chance to work with cutting-edge technologies in a supportive environment. Enjoy the flexibility of remote work combined with access to a state-of-the-art office in Waterside, London, fostering both productivity and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Predictive Maintenance Data Analyst in England
✨Tap into Online Data Science Communities
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Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Predictive Maintenance Data Analyst in England
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Hays, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Hays, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Hays’s attention and show the tangible impact of your work.
How to prepare for a job interview at Hays
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Hays.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Hays.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Hays.
