At a Glance
- Tasks: Help modernise data systems and enable AI-driven automation through scripting and documentation.
- Company: Join LevertonHELM, a forward-thinking company focused on innovation.
- Benefits: Gain hands-on experience, mentorship, and opportunities for growth in a dynamic environment.
- Other info: Exciting career development opportunities await in this collaborative role.
- Why this job: Be part of a team that values curiosity and problem-solving in a fast-evolving tech landscape.
- Qualifications: A passion for technology and a willingness to learn; no prior experience required.
The predicted salary is between 28000 - 35000 £ per year.
Leverton HELM is seeking a junior data systems administrator to help modernize internal data capabilities.
You will learn the architecture of our systems, document connections, and build simple scripts for backups and monitoring while enabling AI-driven automation.
The role emphasizes problem solving, curiosity, and a continuous learning mindset in a fast-evolving environment.
You’ll work closely with the team to maintain workflows, upgrade components, and create internal tools that cut manual
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Junior AI-Enabled Data Systems Engineer in Basingstoke employer: LevertonHELM
At LevertonHELM, we pride ourselves on being an exceptional employer, offering a dynamic work environment in Basingstoke where innovation and safety are at the forefront of our operations. As a Senior SHEQ Advisor, you will not only have the autonomy to influence key business outcomes but also benefit from a culture that prioritises employee growth through continuous training and development opportunities. Join us and be part of a forward-thinking team dedicated to excellence in SHEQ practices while contributing to the rapidly evolving lithium industry.
StudySmarter Expert Advice🤫
We think this is how you could land Junior AI-Enabled Data Systems Engineer in Basingstoke
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Junior AI-Enabled Data Systems Engineer in Basingstoke
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at LevertonHELM, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at LevertonHELM. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at LevertonHELM
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
