Your Guide To Getting Hired in Big Data and Data Science: 2021 Updated

Many believe Big Data and Data Science are the next frontiers for innovation, productivity, and competition. Which is why there are a lot of career opportunities in this field. Are you looking to work in this area? Then check out these simple practical pointers. Here’s a guide to getting hired.

Did you know a recent study revealed that there will be around 140,000 to 190,000 open positions in the field of Big Data and Data Science for 2018? And that’s just in the U.S. alone. MGI and McKinsey’s Business Technology Office made this estimation.

Wondering what’s causing this massive influx of career opportunities in this field? The researchers reported that it was due to the increasing volume and variety of information. Among the prominent information, sources include social media, multimedia, and the Internet of Things.

The need for Big Data and Data Science professionals stretch across various industries. It includes finance, government, technology, pharmaceuticals, and healthcare.

And as the need to filter and collect relevant information increases, the demand for Big Data and Data Science professionals is at its highest today. At present, companies realized the need for people who can analyze and interpret an ever-increasing amount of information in a more economical and efficient manner.

Sexiest Job of the 21st Century

Your Guide in Getting Hired in Big Data and Data ScienceDid you know working in Big Data and Data Science is the sexiest job of the 21st century? This description first appeared in Harvard’s Business Review October 2012 issue.

Is it still the sexiest job in 2018? Will it still be five or ten years from now? Yes, we believe so. Career opportunities and other trends in Big Data and Data Science will continue to rise in number in the next couple of years.

Why? Because data pervades every aspect of our lives.

Without a doubt, there are a lot of career opportunities in Big Data and Data Science. However, it can be a very daunting task for the professionals involved. Imagine handling such vast volume of data. It can be overwhelming.

Are you looking to get a job in this particular area? Planning to start on this career but you’re not sure what to do? Wondering what roles are available in the Big Data and Data Science industry? What skills do you need to have to get hired? Here are a couple of pointers.

Skills Checklist for People Considering a Career in Big Data and Data Science

Whether you’re an experienced IT professional or a newbie, it pays to develop and have the right technical skills to succeed in Big Data and Data Science.


Your educational background and industry experience can help determine where you’ll fit in. Ideally, you need to have good programming skills to work in Big Data and Data Science. A solid foundation in mathematics and statistics will work to your advantage.

Machine Learning

Some large companies require their candidates to have knowledge in machine learning and artificial intelligence. These organizations include those that offer data-driven services like Uber, Netflix, and Google Maps. They generally prefer individuals to be well-versed in ensemble methods, random forests, and k-nearest neighbors.

Calculus and Algebra

For companies that offer products defined by data, algorithm optimization and predictive performance are critical to their day-to-day victories. Thus, comes the need for a professional who knows multivariable calculus and linear algebra.

Data Wrangling, Visualization, and Communication

Data distillation is a messy job. There’s going to be a lot of imperfect data that needs to be filtered or completed. These imperfections include missing values and inconsistent string formatting.

On the other hand, data visualization and communication are crucial elements in a data-driven business environment—where decision makers heavily rely on precise data. It is immensely helpful for these decision makers to have all the data they need in order to properly visualize the playing field. Then come up with a well-informed, intelligent decision.

Getting Started in Big Data and Data Science Careers

Job hunting isn’t an easy task. It can be challenging. It can be frustrating. So if you’re looking to land a job in Big Data and Data Science, these pointers can help you.

Connect on LinkedIn

Want to get the attention of the right people? Sign up for a LinkedIn account. Then send connection requests to data scientists. It’s about building your own network and tapping it. You can send a message to certain people that you’re interested in filling a Big Data and Data Science position.

Develop the Needed Skills

Read about the required skills in Big Data and Data Science careers. Pick a skill or two and develop it. Don’t forget to add your selected skills to your LinkedIn profile.

Take Every Interview You Can

Interviews are traditionally a means to secure a job. But what if get scheduled for an interview with regards to a job that you don’t particularly like? We advise that you still proceed with that meeting. Use that as an opportunity to develop the communication skills. Look at it as your preparation for the interview for the job you like.

Decline Unfavorable or Disadvantageous Offers

If the position isn’t exactly what you’re looking for, decline. Learn to let go of “opportunities” that are rather unfavorable or disadvantageous to you.

Embrace the Disappointment

Didn’t get the job you’re hoping to have? That’s OK. There’s a lot more in the job market. Embrace the disappointment. Vent out to your boyfriend/girlfriend/husband/wife/partner. Call a sibling. Or hit the gym and blow off steam. And when you’re done, loop back and do it all over again.

Job Roles in Big Data and Data Science

When you speak of “data scientist,” the position covers a wide range of specialties. It’s not limited to business analytics. Data scientists don’t just filter out information; they also intervene in building software platforms and data products.

A data scientist may act in any or all of these capacities:

• Data Engineer or Architect
• Data Administrator
• Analytics Manager
• Data Analyst
• Business Intelligence Manager

Knowledge in these programs will fetch a bigger salary rate or more flourishing career opportunities.

• Python
• Java
• Hadoop
• R