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For Companies At a Glance
- Tasks: Analyse data to uncover trends and present findings to management.
- Company: Join a growing company with centres across the UK, focused on retail and manufacturing.
- Benefits: Enjoy a stable office environment with opportunities for professional growth.
- Why this job: Be part of a dynamic team that drives business improvement through data insights.
- Qualifications: Experience in data analysis tools like SQL, Python, and Power BI is essential.
- Other info: This role is 100% office-based, Monday to Friday.
The predicted salary is between 28800 - 48000 £ per year.
Our client continues to expand their business, with centres throughout the UK. As part of their expansion, there is a new vacancy for a data analyst, with experience of working in a retail, manufacturing or automotive sector, to join the company at offices on Gillingham Business Park.
Skills & Experience:
- Proven work history as a data analyst, able to demonstrate a strong proficiency in using analysis tools such as SQL, Python, R, Excel etc.
- Experience of Power BI or similar
- Familiar with the concepts of databases and data warehousing
- Experience in analysing large and complicated data files
- The ability to communicate well, able to explain technical concepts to non-technical stakeholders
- To be detail orientated, able to ensure data accuracy
- To be inquisitive with an analytical mindset, able to solve complex problems
Role & Responsibilities:
- Able to process map the entire operational journey, able to highlight areas of suggested improvement to stakeholders
- Present findings to Senior Management
- Ensure accuracy across various platforms
- Identify potential gaps in current systems and usage
- Analyse data, identify trends to uncover patterns and insights that drive business improvement
- Collaborate with other departments
Monday to Friday: 100% office based.
Data Analyst employer: Qube Recruitment
Contact Detail:
Qube Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as SQL, Python, and Power BI. Consider taking online courses or tutorials to sharpen your skills in these areas, as practical knowledge can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the retail, manufacturing, or automotive sectors. Attend industry meetups or webinars to connect with potential colleagues and learn about the latest trends and challenges in data analysis within these fields.
✨Tip Number 3
Prepare to discuss your previous experiences in analysing large datasets. Think of specific examples where your insights led to business improvements, as this will demonstrate your ability to add value to the company.
✨Tip Number 4
Practice explaining complex data concepts in simple terms. Since the role requires communicating with non-technical stakeholders, being able to convey your findings clearly will be crucial during interviews.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a data analyst, particularly in retail, manufacturing, or automotive sectors. Emphasise your proficiency in SQL, Python, R, Excel, and Power BI.
Craft a Strong Cover Letter: In your cover letter, explain how your analytical mindset and problem-solving skills can benefit the company. Mention specific examples of how you've communicated technical concepts to non-technical stakeholders.
Showcase Relevant Projects: If you have worked on projects involving data analysis, include them in your application. Describe the tools you used, the challenges you faced, and the outcomes of your analyses.
Proofread Your Application: Before submitting, carefully proofread your application for any errors. Ensure that all information is accurate and that your documents are well-formatted and professional.
How to prepare for a job interview at Qube Recruitment
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in SQL, Python, R, and Excel during the interview. Be prepared to discuss specific projects where you used these tools to analyse data and derive insights.
✨Demonstrate Your Analytical Mindset
Prepare examples of how you've tackled complex problems in the past. Discuss your approach to analysing large datasets and how you identified trends or patterns that led to business improvements.
✨Communicate Clearly with Non-Technical Stakeholders
Practice explaining technical concepts in simple terms. You may be asked to present findings to senior management, so being able to convey your insights clearly is crucial.
✨Be Detail-Oriented
Emphasise your attention to detail and commitment to data accuracy. Share instances where your meticulousness has positively impacted a project or decision-making process.
