If you’re one of those people who has that one CV and sends it to dozens of different job applications, you definitely need to read this article.
CV is the first encounter your potential employer has with you. That means it has the power to either make you or break you. And, if you don’t invest enough effort into optimizing your CV for specific job applications, you’ll end up in the rejection pile with the rest of applicants who failed to amaze.
The same goes for job applications in data science. You have to optimize your CV to fit the specific requirements of a data science job application. By doing this, you’re significantly improving your chances of getting that interview call.
That’s why we’ve put together this guide, to help you optimize your CV.
Let’s take a look at the 8 best ways to optimize your CV for a data science career.
1. Examine the Job Application
First things first, you need to understand that for each individual job position you plan on applying to, you have to make the right changes in your CV.
Think of it this way- no CV can fit two different job applications.
This is why, before you start optimizing your CV, you need to examine the job application thoroughly. Here’s what you need to know:
- company information
- company goals
- their expectations for the person they hire
- required skills and education
- every specific detail that might come in handy
Make sure that you read the job opening description several times until you’ve fully understood what it’s about.
Then, use that information and incorporate it into your CV to make it more suitable for the specific job application, and thus more successful.
2. Data Scientist Personal Statement
In order to make your CV stand out, you have to think about those job recruiters who read dozens of more or less the same CVs every day.
You need to write a killer opening statement to make sure your CV is the one that shakes them up a bit.
A data scientist opening statement needs to be:
- short and concise
- packed with the most valuable information
Also, this opening statement has two goals:
- to briefly describe who you are and what’ you’ve done so far
- to show your goals and business ideas
- show the reason why you’re applying for the job
Make sure it’s a single paragraph, no longer than 4-5 lines.
3. Experience & Achievements
Once again, the key to success is knowing what the job recruiters are looking for and how you can fit their vision of the perfect employee.
This is why you won’t do any of the following:
- list data science unrelated experience
- extensively describe individual experiences
- note everything you’ve ever done
Instead, you have to be very clever and select the experiences and achievements that the job recruiters are looking for.
So, if the job description says nothing about necessary AI skills, don’t mention them.
Here’s what you need to do:
- prioritize your experiences
- put the most relevant ones first
- write with the job description in mind
If you accidentally overdo it, you’re come across as boastful, unprofessional, and even boring.
4. Describing Projects & Previous Job Positions
Job recruiters will want to know about the specific details for every previous job position you’ve held or job experiences. But, you should list it carefully and concisely.
So, instead of writing extensive and long paragraphs about the millions of assignments you had to cover while on a certain job, you have to take a step back and think.
Answer these questions:
- What are my most valuable achievements in this job?
- What did I learn from this experience?
- How did this experience make me a better data scientist?
Yes, once again you need to prioritize and share only the most valuable and important information with your future employers.
Going into too much detail is unnecessary and will reject them.
5. Nail the Education Section
When you’re optimizing your CV for any career type, the education section is a must. Still, most people don’t make as much use of this section as they could.
For most people, the education section should state:
- college name
- college location
- years of attending college
But, there’s more you can do with this section.
Once you state the above mentioned, proceed to making a connection between your formal education and data science.
To put it simply, explaine what you’ve learned and done during college that’s related to data science and even your current skills and knowledge.
6. Insert Keywords
When we’re talking about optimization, keywords are important.
You never know who’s going to be making that first selection of CVs- a human or a system and an algorithm?
This is why you have to:
- find the right keywords
- insert them into your CV naturally
- make your CV more appealing
You can even use a keyword generator if you need help or inspiration.
Choose the keywords based on the job description, company type, and other specific details.
7. Use a Simple, Light Design
Even though the main focus of your CV should be the written content, the visual aspect will play a significant role as well. Here’s why.
If you choose a design that is overly complicated, colorful, hard to scan, and impossible to read quickly- you’re doomed.
No job recruiter wants to spend their precious time looking for specific information or trying to find their way through your CV.
Plus, they expect far better organizational skills from a data scientist.
This is why you should focus on a simple design:
- clean outline
- simple font
- visible headlines for each new section
- short paragraphs
- short sentences
- lists and bullet point are preferred
In addition, try fitting your entire CV to a single page. This will additionally impress the recruiters and tell them you’ve only put the most important information in your CV.
We know you’re not chasing a career in design, but aim for simplicity and your CV will have much better chances of winning you’re the interview.
8. Watch Your Accuracy
As a data scientist, you have to be detail-oriented, patient, and observant.
But, it’s not enough for you to just list these characteristics in your CV. You have to show them.
Luckily, your CV gives you a chance to show just how professional you are. All you have to do is watch your accuracy and ensure your CV is completely polished before you send it out.
Here’s what you need to do:
- proofread several times
- remove grammar and spelling mistakes
- choose the right vocabulary
- watch sentence structure
As you can see, optimizing your CV for a data science career is challenging but doable. You have to invest yourself in the process, and create a strategy that will work every time.
The list above provides all the essential steps for making your data science CV successful. Use those tips and start optimizing your CV today.
Dorian Martin is an experienced writer, who turned his passion for the written word into a career. He is a content writer and marketing specialist, always sharing advice and information with the goal of helping his readers and clients improve their professional and private lives. He also works as an editor and content creator for dissertation writing services review site.