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- Tasks: Analyse learner data to identify trends and support curriculum teams.
- Company: A UK charitable organisation dedicated to making a difference.
- Benefits: Hybrid working model, pension, and generous holiday allowance.
- Why this job: Make an impact in education while developing your data skills.
- Qualifications: Expertise in data visualisation, SQL, and PowerBI required.
- Other info: Work Monday to Friday, 9am to 5pm in a supportive environment.
The predicted salary is between 30000 - 42000 £ per year.
A UK charitable organisation is seeking a Data Analyst to manage and maintain reporting functions. The role includes analyzing learner data to identify trends and supporting curriculum teams.
Candidates should have expertise in data visualization, SQL, and PowerBI.
This position offers a hybrid working model, pension, and generous holiday allowance. The successful candidate will work Monday to Friday from 9am to 5pm.
Data Analyst - Learning & Training Insights (Hybrid) employer: Personnel Selection
Contact Detail:
Personnel Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Learning & Training Insights (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the organisation on LinkedIn. A friendly chat can give us insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data visualisation projects, especially using PowerBI. This will help us demonstrate your expertise and make you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your SQL skills and be ready for technical questions. We recommend doing some mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect directly with us.
We think you need these skills to ace Data Analyst - Learning & Training Insights (Hybrid)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data visualization, SQL, and PowerBI. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data analysis and how you can contribute to our mission. Keep it engaging and personal – we love a bit of personality!
Showcase Your Analytical Skills: In your application, include examples of how you've used data to identify trends or support decision-making. We’re looking for candidates who can demonstrate their analytical prowess, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the role and our organisation there!
How to prepare for a job interview at Personnel Selection
✨Know Your Data Tools
Make sure you brush up on your SQL and PowerBI skills before the interview. Be ready to discuss specific projects where you've used these tools to analyse data and create visualisations. This will show that you not only understand the tools but can also apply them effectively.
✨Understand the Organisation's Mission
Since this is a charitable organisation, take some time to research their mission and values. Be prepared to explain how your work as a Data Analyst can support their goals. This will demonstrate your genuine interest in the role and alignment with their objectives.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical problems or analyse data trends. Practice articulating your thought process clearly. Use the STAR method (Situation, Task, Action, Result) to structure your answers, which will help you convey your analytical skills effectively.
✨Showcase Your Teamwork Skills
As you'll be supporting curriculum teams, highlight any previous experience working collaboratively. Share examples of how you've communicated insights to non-technical stakeholders, as this will illustrate your ability to bridge the gap between data analysis and practical application.
