The resume button alone is more than enough to hit the “Hire” button. But wait, why doesn’t it work when it comes to looking for jobs in data science or any other new-age technology jobs. Job hunting has always been challenging, even for those with technical skills.
Today it has been challenging as ever for employers to choose between two qualified professionals extensively looking for jobs.
If data science is so much in-demand why is it difficult to land a job?
Perhaps it’s because your skills are not aligned in the right way they’re supposed to in your resume.
Building an effective data science resume should be done strategically. In simple words, you need to have the right set of words to be used, relevant projects to showcase your skillsets, and can tell your story effectively.
Here are the details a data scientists should add in their resume: –
- Create an effective structure for your resume
Ensure the overall structure of your resume has been pre-defined. This will help you understand the details and different sections you need to add to your resume.
- Know the right length
Gone are those days where you add every minute detail to your resume. Remember you’re building a resume for a technical job role. Employers are not interested in your sentence formation or resume design but the knowledge in the latest technology skills.
To be precise a single-page resume is more than enough to showcase your skillset. Any resume beyond two pages is likely to get rejected.
- Define separate segments
Once you’ve finalized what should go on your resume, it is time you need to place this information in the right sections.
Core areas your focus should be upon: –
- Contact details should not eat up extra space
- Experience – in years
- Projects completed
- Data scientist skills
- Awards and accolades
- Website links for projects done online
- Addition of the right and relevant information to your resume
Here’s what will draw the attention of the top employers looking to hire you.
- Prioritize your information
A professional building a resume to launch their first data science career must know about the right set of skills and information that needs to go in this section. You need to be careful about providing all the details in this section without adding any irrelevant information.
For instance, if you have worked on Natural Language Processing (NLP) project or have solved a problem and have applied for an NLP data scientist job role. But the projects mention is related to beginner level machine learning challenges then this might become risky as there are high chances the recruiter may reject your resume.
- Crisp and short
Content added on the resume should be short and crisp. Avoid fluff, add only what is relevant. Ensure the sentences should be in the active voice, this makes the reader easily understand your language.
- Obtain feedback from industry experts
Now that most information has been added to your resume, you might need a final check. It is always advisable to get feedback from somebody working in the industry. This is crucial because at times there are key points that you might have missed out or may tend to overlook the flaws. To avoid making these mistakes you need to get your resume reviewed by the right industry experts.
- Create a digital buzz of yourself
With technologies growing at breakneck speed, a data scientist needs to upgrade and stay in sync. Certifications in data science provide credibility to the candidate’s resume. A certified data science professional has the advantage of demonstrating their achievements by highlighting it in their LinkedIn profile.
Along with this, the candidate can upload their GitHub profile showcasing the projects they’ve worked upon.
This is a mandatory checklist for all tech professionals looking to grab a job in new-age technologies.