Getting back into the data science field after a break can be tough. But what if you’ve been working on personal projects to keep your skills sharp? Should you highlight them prominently on your CV or tuck them away in a separate section?
I’ve been in a similar situation, and I’ve learned that showcasing personal projects can be a great way to demonstrate your skills and enthusiasm to potential employers. So, where should you put them on your CV?
Why Personal Projects Matter
Personal projects show that you’re proactive, motivated, and committed to staying up-to-date with industry trends. They can also fill in gaps in your work history and provide concrete examples of your skills in action.
Where to Put Personal Projects on Your CV
There are a few options, but here’s what I recommend:
- Create a separate section: Consider adding a section specifically for personal projects, such as ‘Personal Projects’ or ‘Data Science Initiatives’. This keeps them separate from your professional experience but still highlights your achievements.
- Include them in your professional experience: If the project is directly related to your previous work experience, you could include it in your professional experience section. This can help to demonstrate your skills and accomplishments in a real-world setting.
- Use a hybrid approach: You could also create a separate section for personal projects and then highlight the most relevant ones in your professional experience section. This way, you’re showcasing your best work while still keeping everything organized.
Tips for Showcasing Personal Projects
- Be selective: Only include projects that demonstrate your skills and achievements in data science.
- Provide context: Briefly explain the project, your role, and what you achieved.
- Include visuals: Add charts, graphs, or images to help illustrate your points and make your project more engaging.
Final Thought
Remember, the key is to showcase your skills and achievements in a clear and concise manner. By highlighting your personal projects in the right way, you can increase your chances of standing out to potential employers and getting back into the data science field.