Student Voice Data & Insights Assistant

Student Voice Data & Insights Assistant

Internship 31500 - 38500 £ / year (est.) No working from home possible
Kingstonstudents

At a Glance

  • Tasks: Collect, analyse, and visualise student feedback to drive impactful decisions.
  • Company: Kingston Students’ Union, dedicated to enhancing student representation.
  • Benefits: Gain valuable experience, flexible hours, and a supportive team environment.
  • Other info: Join a vibrant community focused on student success and representation.
  • Why this job: Make a real difference by turning student voices into actionable insights.
  • Qualifications: Strong analytical skills and a passion for student engagement.

The predicted salary is between 31500 - 38500 £ per year.

Kingston Students’ Union in Kingston upon Thames is seeking a Data & Insight Assistant (Student Voice) to help turn student feedback into actionable insights and support evidence-based decisions.

In this role you’ll work with the Student Voice & Insight Team to collect, analyse and visualise data, maintain engagement records and collaborate with colleagues across the Union and university to strengthen student representation.

#J-18808-Ljbffr

Student Voice Data & Insights Assistant employer: Kingstonstudents

At Kingston Students' Union, we pride ourselves on fostering a vibrant and inclusive work culture that empowers our employees to thrive. As a Sports Activities Assistant, you'll not only gain invaluable experience in sports leadership and event management but also enjoy the unique advantage of working within a supportive community dedicated to enhancing student life. With opportunities for personal growth and development, we encourage all team members to bring their passion and creativity to the forefront, making a meaningful impact on our student community.

Kingstonstudents

Contact Details:

Kingstonstudents Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Student Voice Data & Insights Assistant

Join Data-Science Meetups

Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.

Utilise University Career Services

Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.

Show Off Your Stuff on GitHub

If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.

Apply Directly on Our Website

Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.

We think you need these skills to ace Student Voice Data & Insights Assistant

Data Collection
Data Analysis
Data Visualisation
Engagement Record Maintenance
Collaboration Skills
Communication Skills
Insight Generation

Some tips for your application 🫡

Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!

Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Kingstonstudents will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!

Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!

Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!

How to prepare for a job interview at Kingstonstudents

Brush Up on Your Coding Skills

As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.

Show Off Your Projects

Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Kingstonstudents.

Know Your Stats and ML Basics

Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.

Be Eager to Learn and Adapt

Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Kingstonstudents that you’re not just looking for experience, but that you're keen to contribute and grow within the team.