10 essential tips to improve your Big Data resume

by Ben Taylor 4 years ago 8 min read

As per current job search trends, big data is amongst the top 5 emerging jobs according to LinkedIn’s 2017 US Emerging Jobs Report.

But it’s not easy to get a big data job because the competition is immensely aggressive. Several steps and stages are meant to be crossed before you can finally get your hands on your dream big data job. Just possessing the necessary skills isn’t enough – you need to know how to showcase the same on paper as well.

To help you do just that, we’ll tell you the 5 key essentials of a big data resume so that you are a step closer to getting your dream job. These tips will easily help you overshadow a vast majority of the applicants out there.

Without further ado, let’s begin.

Compile all information in one place before you begin

The art of unlearning is a habit we are all guilty of. However, this may do more harm than good, especially when you’re on the crossroads of a job switch or looking to land your first big data job.

When it comes to creating your big data resume, you might find yourself at loss of words just because you are unable to recollect important pieces of information.

A trick that can help is to start off by compiling all your information in one place before you even begin working on your resume. Compile all relevant and not-so-relevant information – starting from achievements in school to internships, work experience and freelance projects you may have done.

Doing this will see to it that you don’t have to run around looking for information that you may want to write in your resume. It also ensures that your big data resume has all the information it needs to champion your case.

On a weekly/monthly basis, make it a point to update this “master resume”. It can contain everything – from you winning the school relay race to a failed startup in college. Remember, it’s for your eyes only. But you never know what you can showcase as a skill that might be required in a potential job opening.

Even if the master resume is 10+ pages, it’s alright. Your job would then be to just cherry-pick the relevant information and achievements for shaping your final resume.

Choosing the correct format for your big data resume

Choosing the right resume format is very important.

Everyone has a different professional history. While some of you may have extensive work experience to show in your resume, some of you might have career gaps that you want to conceal in your big data resume.

Whatever the case may be, you can choose either one of the resume formats given below that works the best for you.

Reverse Chronological Resume Format: If you have extensive work experience with no career gaps, then make your big data resume using this format. In this format, the Professional Experience, Education and Certifications sections are written in reverse chronology, meaning the most recent profile/education is written first, dating back to the oldest one.

Functional Resume format: Here, the emphasis is given on skills rather than roles. This is suitable for professionals who are frequent job switchers, or who want to hide a career gap in their resume. You can club all your contributions across all your profiles and group them under relevant ‘functions’. It’s the least preferred resume format for recruiters, and we don’t recommend this format as well.

Combination Resume Format: In this format, your work experience and your skills are given equal weight. It combines the best of both functional and reverse-chronological resume format. While the reverse chronological format is the one most preferred by recruiters, you can opt for this format in case you want to deviate.

Start with the Professional Experience section first

A great tip to kick off your big data resume is to begin by working on the Professional Experience section first. This is the best way to proceed as this is the heart of your resume. Here’s what you can do here:

Use achievement figures wherever possible

If hundreds of professionals are applying for a single big data profile, suffice to say that they’d have similar skills – more or less. How do you think the recruiter will distinguish your resume from everyone else’s?

Numbers.

Everyone uses the same techniques and algorithms when presented with a problem. How did you use it though? What was the quantifiable impact you were able to deliver?

That’s what figures are for. Adding numbers (even ballpark ones) in your resume will significantly help you overshadow your competition. It will allow the recruiter to gauge the scale of your contributions and accordingly assess how much of an impact you’ll be able to make in their organization.

For instance, every data scientist will write segmentation, clustering, predictive models, etc. in their resume. But how did you use them to benefit the company you were in? Let’s clarify that using two examples:

“Used predictive models to analyze the market and cut costs”

“Designed predictive models to scrutinize market competition and slash costs by USD 500k”

In case you didn’t notice, you can also bold key numbers and phrases to direct the attention of the recruiter to where you want.

Use one-liner points to talk about your big data skills

It’s high time to skip lengthy paragraphs and resort to using one-liner points to document the details of your professional experience as a thriving big data professional.

Example:

Led a team of 10+ engineers and coordinated the QA effort in liaison with 5 departments
Designed predictive models to study market competition and reduce costs by USD 500k
Generated segmentation models using K-means Clustering to identify 100k+ new users

This is an example of Princeton-based action-oriented accomplishment statements. Incorporating this methodology while you’re framing points in your resume will catapult your chances of getting shortlisted.

Put the Key Skills and Summary sections at the end

When making your big data resume, once your key sections are done and dusted, pick up the Key Skills Section and then close it off with a crisp Summary section in the end.

It will be easier to make these sections towards the end as you can scan your big data resume to look for relevant big data skills that can help you get that coveted Big Data Engineer job that you’ve been chasing.

Once the Key Skills section is done, it will be easier for you to write your big data resume summary section. In the summary, instead of merely mentioning the skills (from the Key Skills section) again, write 3-4 lines detailing how you can use the skills mentioned below to deliver an impact. Keep it less jargon-heavy and more impact-driven.

Now that you have all your skills at one place, you can incorporate 4 – 5 major skills in your summary to explain how you can leverage these skills to benefit the next organization.

Make use of power verbs, bucketing and bolding

Have you practiced the art of using resume power verbs to describe your roles & responsibilities in the Professional Experience & Internships section of your Big Data Resume?

If you haven’t, now’s the time to start.

Begin each one-liner point with a power verb in present continuous tense for present profiles and in the past tense for past profiles. If the number of points is more than 4 in any work experience, then club similar points together under a relevant bucket.

Group similar points under unique subheadings (bucketing) to maximize the visibility of your roles & responsibilities, and highlight important achievements in each line by marking them in bold (bolding).

The best part?

The Siamese twins we call “bucketing & bolding” together act as a powerhouse for increasing the readability of your big data resume.

Making the resume header in the correct way

The header is the very first section of your resume. Its job is to communicate the identity of the resume holder before the recruiter.

So as a rule of thumb, do not label your Big Data Resume as ‘Resume’ or ‘CV’. Simply write your real full name at the extreme top part of your resume.

As a data science professional, you are also expected to be active on various platforms like LinkedIn, GitHub, Kaggle, etc. In case you have a thriving presence in any or all of these platforms, you can go ahead and include them in the header section.

There’s no point in mentioning them if the recruiter will be redirected to a profile that was last updated many moons ago. Only do it if it’ll add value to your overall profile, otherwise skip it.

Only provide the required personal information

The personal information section is the second section of the resume. All that you need to write in it is one mobile number, one professional email address (not affiliated to your current/previous organization) and the city/state where you are living.

In general, do not provide details of your religion, date of birth, marital status, etc. as they are not required and shouldn’t go into a resume. That being said, a lot will depend on the country you’re targeting. In the US for instance, it’s prohibited to include your gender, age, race, religion, etc. in your resume. In the Mid-east, however, they ask for your passport details along with your date of birth.

Make it a point to go through the hiring guidelines before you send your resume across.

Do not exaggerate your profile title

While making a big data resume, many people either forget to write a profile title or make the common mistake of over-glorifying their profile title.

Since the field of big data is very vast and there are multiple profiles in this field, it is important to communicate your exact role in your profile title without any gross exaggeration.

Example:

If you’re a Big Data Architect, your profile title should read “Big Data Architect”. Let’s say you’re a Big Data Architect and are targeting a job listing for Data Science Lead.

Don’t try to fool the recruiter by writing Data Science Lead in the profile title. Stick to the truth – that’s the only way you can realize your potential in the long run.

Follow the correct format for writing the education section

When writing the education section, first write the name of the university, and then write the name of the course you have pursued. Use the city name and country code format to write the location of the university and mention both months and years while writing the dates for enrollment and graduation from the course.

In case you don’t have much relevant experience around data science, you can go ahead and include the modules you covered as part of your degree. These modules would comprise the keywords of your target profile and will go a long way in bridging the gap between you and your dream job.

List your conferences, training, certifications, publications correctly

If you have any conferences to include in your big data resume, then you need to follow the correct format to write them.

Start off with writing your role in the conference followed by the topic of discussion and conference name.

After you do this, write the date on which the conference was held and the location where the conference was held.

Follow a similar approach for all other sections like Training, Certifications, Publications, Patents, etc. Include as many details as you can without breaching the 2-page limit, and ensuring that you’re only using one-liner bullet points (or sub-bullet points).

Complete Sample Resume for a Big Data Professional

This brings us to the end of the 10 essential tips for writing a Big Data Resume.

In these tips, we’ve covered everything under the sun when it comes to customizing your resume to get the big data job of your dreams. Incorporate these teaching in your resume and you are good to go.

To get a clear idea of how your resume will look like after incorporating the above tips in it, take a look at the below-given sample.

Hope the sample above would have addressed any pending queries. Got any more? Feel free to drop a comment below!