How to Create a perfect CV for a Career in Data Science
By: Kristin Mack
Tags: Data Engineering, Data Science Careers, Data Science, Data Scientist, Machine Learning

You have approximately 7.4 seconds to showcase your skills! And your time starts the minute your CV goes into the hands of the hiring manager.

Sweating, are you?

Too little time to even be noticed, let alone make an impression.

Right?

Wrong!

It’s the maximum time a hiring manager will spend on any resume; some may even go quicker than this.

To ensure that your CV pass the screening test and stand out from the crowd, follow these simple steps -

Be visible Articulate your Ability Be Visual Showcase your process Stand out from the crowd

Remember, the competition for the data science position is fierce, as the vacancies tend to increase dramatically. Result: There is a surge in the number of data science professionals.

Despite the cut-throat competition there’s lots of ambiguity surrounding the role. Not surprising considering the fact — Data Science is a vast field and a broad term and hiring a right fit for the role can be a daunting task.

You can make it easy for the recruiter and for yourself as well.

Let’s see what does an employer seeks in a resume of a data scientist.

To know what the employer wants, let’s don the hat of a hiring manager and then scan through the CVs.

According to the industry experts, these are the skills that will make an employer stop in her tracks and give your resume thorough look -

Education (either a Bachelor’s degree or a Master’s degree in Computer Science, Social Sciences, and Statistics) R programming Python Coding Hadoop platform SQL database/coding Apache Spark Machine Learning and Artificial Intelligence Data Visualization Unstructured data

Now the question — how are these skills placed in your portfolio to gain that attention? Scan your resume and follow these tips so as to make your CV attractive to a hiring manager.

Tip 1: Place the ‘in-demand’ skills on the top:

You want your resume to catch the eye of a recruiting manager, put the ‘in-demand’ skills on the top of your resume. The recruiting manager won’t have to scan through the entire resume to pick up your skills. Note: Avoid using one column bullet list for skills. This will take up lots of space on your CV, instead place them in one sentence or take the help of a designer to differentiate each skill creatively.

Skills: R Data Science Data Analysis Statistics Machine Learning Predictive Analysis Python Artificial Neural Networks

Tip 2: Place your achievements in a detailed and concise manner:

This again has to be on the top half of your resume. Remember this is also critical like your skills. In addition, this is your ‘show’ part not the ‘tell’ part. This is your area where you need to draw in the recruiters with your strengths before they even start looking for your flaws.

Do it right by following these steps:

Talk about relevant achievements

Impress them with numbers

Floor them with one sentence per achievement

Note: Use the following terms to describe your achievements — Skill, Activity, Result to make your point clear.

Tip 3: Don’t list your non-technical skills, explain them:

Don’t make the mistake of simply listing your non-technical skills, as that will not make any sense to the recruiters. For instance, if you just write ‘Verbal Communication’ it won’t make much sense to the person scanning your resume so you need to write it in detail.

Some examples include:

Doesn’t this look more appealing? Yes, so now you understand the importance of explaining your non-technical skills.

Tip 4: Match Keywords with the job description:

Employers often use keywords when giving the job description (JD) for the positions. Usually the recruiting managers put the names of the qualifications, certifications, technologies, and skills in the JD.

Some of the keywords that you should include in your resume are: machine learning, software engineering, Python, fast prototyping, written and verbal communication skills.

Note: While it is important to stuff your resume with these keywords, it is suggested not to overdo it, as that can backfire.

Tip 5: Strengthen your skills with certification programs:

The certification programs available online help you cement your skills. Data Science Certifications will help you not only in getting those skills validated but also ensuring that you are ahead of the competition with latest tools and technologies being covered in the certification curriculum.

Tip 6: Gain hands-on experience:

Internships, or finding a problem on your own and trying to get the results from the data collected will help you gain that coveted experience. While doing your own thing is a good way, it is advisable to go for internships in the beginning to build on the technical knowledge.

Remember to keep your resume short and crisp, with skills highlighted as mentioned above. Create a new resume based on the above-mentioned tips and send it out and wait for that call.