Data Science Jobs in 2019: Trends, Analysis, Expectations and Opportunities

Data Science Jobs in 2019 have increased exponentially.

According to LinkedIn, one of the most budding jobs in 2019 is that of a data scientist. Data Scientist topped the LinkedIn’s list of the Most Promising Jobs of 2019. This booming field held the 9th slot in the last year i.e., 2018. Incredible growth, right?

Do you know what does this mean? Did someone say more job opportunities? Well, I’d be astonished if someone had said confusion; simply because job opportunities have definitely increased and more opportunities translate into a confusion of what to expect from the job market and the candidate too. You’d also wanted to know what is trending in the job market; how to approach this ever-growing field; what was the salary trend; what can you expect from the market and how to approach it.

Worry no more! Read on to find the answers to all your queries and easily trace the data scientist job market in 2019. Here is what to expect from this post.

Knowing the prevalent trends in the data science job sphere
Tracing the learning path
Recognizing the right steps to get the dream job
Analyzing if it is actually worthy to become a data scientist
Witnessing one of the recent examples that shows the effects of the unparalleled hype in data science

Data Science Job Trends 2019

It is a known fact by now that be it the biggies like Google, IBM, Deloitte or other small players, everyone needs a data scientist to transform the heap of numbers into actionable insights. One of the biggest trends that has been there, unperturbed, is the steep hike in the demand for trained and skilled professionals.

Here are some of the data science job trends that are evident in 2019 (and will be widespread for the next year).

Vacancies

India’s share in the open job positions all over the world is 6%. Most of the job openings in the data science field are full-time (97%), while not much (3%) are contractual or part-time. Do you know how many total jobs are there in the field (as of February, 2019)? The number is huge- 97,000.

Data Science Opportunities in India 2019

Experience in Programming

The trend prevalent in the data science field is that programming is a must to get the job. 48% of people think that programming doesn’t need a prior training and this can be acquired on the job. For 45% of people, programming is vital to establish a career in data science. There were remaining 7% of the people, for whom programming was not an important attribute of the field.

Data Science Programming Experience 2019

Most Favored Cities (in terms of employment)

While most cities are still on the way to completely step into the realm of data science job sphere, other cities are already a hot favorite, in terms of offering job employment in 2019. The silicon valley of India, Bengaluru is the most favored city, leading with 81%. 15% of this distribution includes Delhi NCR, Mumbai and Hyderabad and the remaining 4% are other Indian cities.

Most favored City (in terms of Data Science Employment) 2019

Work Experience

Cited as an aid to get into data science field but not a mandatory one, similar work experience was also one of the most debated trends in the first half of 2019. For 44% of the people, work experience is substantial but not critical. But 36% of the people opined that having work experience is extremely important. The remaining 20% of the people believe that being experienced is not at all important to get a job in the field.

Preferred Mode of Job Search

Job aspirants prefer different modes to search for their ideal job; you might prefer LinkedIn, a professional way but your acquaintance might opt for contacting his connections in the industry. In the first half of 2019, a whooping 51% preferred LinkedIn to search for a job in this field. Naukri.com, the favorite job portal, holds the second slot with 18%. This is followed by 19% of the people who make use of other job portals and mediums. The remaining 12% of the people wish to contact acquaintances and friends to know about the job opening.

Favorite Industry to Work in

While almost every industry generates data and thus is the application industry of data science, still there are only three industries that are the most favorite among the job seekers. These are- banking with 32%, customer service with 21% and social media with 18%. The remaining 29% include various industries like medicine, government, environment, transport and ambiguous.

Data Science Favorite Industry to Work in 2019

Most Promising Job Sectors (with increased number of opportunities)

There are industries that are the favorites of the data science aspirants and then there are some of the industries that are the hotspots in hiring more number of data science professionals. As deemed, IT sector leads this list with 36%, followed by e-commerce and banking at 24% and 22%, respectively.

Primary Language Skill (important programming language for data science aspirants)

If you are an aspiring data scientist and are well versed in at least one programming language, you are already well-off. Do you know Python emerged the clear winner, with 75%, as the number one language prerequisite? This is an imperative skill to get you through to a job. R was the second favorite with 18% and SAS at 3%.

Data Science Salary Trends, 2019

The average base pay of a data scientist is ₹950,000 p.a. This was the trend in the first half of 2019. For the second half, it is anticipated that the base salaries may remain the same. The salary will also depend on the role and how skilled a professional is. With organizations opting for cloud, professionals skilled in tools like Hadoop, Spark etc. are more in demand and the employers are ready to shell out a good amount to hire them. Are you skilled in Python? Expect to bag a handsome package.

En-route to being a Data Scientist in 2019

Once you are en-route to become a data scientist, there are many things you should know about. Think that data scientist is the only job title in this field? Give it a second thought. To start with, here are the job titles in the field of data science (in the order of hierarchy).

Data Scientist
Business Analyst
Data/Analytics Manager
Business Intelligence Manager
Data Administrator
Data Architect

Now, here are the steps that you need to take en-route to become a data scientist.

Knowledge of Basic Statistics and Maths

A combination of fundamental and advanced statistics like distributions, hypothesis testing, probability, inferential statistics and Bayes theorem will work best for you. When you use statistics, you will aid the stakeholders in designing and evaluating experiments and taking measured decisions. In order to build your own implementation models, you need to have a strong understanding of the applied mathematical concepts like linear algebra and multivariable calculus.

Python

One of the easiest programming languages to be mastered, Python is the hot trend in the first half of 2019. This is one programming language that works across platforms and is widely adopted. You need to get started with Python and move ahead in the field.

Knowing and Applying Elementary Machine Learning Concepts

The key is to start with some basic machine learning concepts and then move on to the advanced ones like time series methods, supervised and unsupervised learning, regression models and algorithms etc. Along with this, you need to have a practical knowledge about where to apply these concepts. Hence, do take up few projects too.

Getting Introduced to Deep Learning

The next step in your journey to set foot in the field of data science is getting introduced to Keras, neural networks and advanced neural networks. This will be a justifiable move after you have gone through the machine learning module.

Create and Maintain Profile and Resume

GitHub and LinkedIn profile will work as magic for you in your job search, if you keep them updated. Creating these profiles and regularly updating them with your recent projects, competitions participated in, will speak volumes about you to your potential recruiters.

Work on Use Cases and Case Studies

Along with updating your profiles, work on your own use cases and case studies. This will give ample of practice and make you ready for actual projects. Staying updated and knowing what’s happening in the industry will weave magic for you.

Did You Take the Right Step in Your Job Search?

Okay! So, now when you are on aggressive job hunt for that perfect job. How you will ensure that you are steering your efforts in the right direction? The right step would be to know where you can find your dream job. LinkedIn and Glassdoor are a few of the most popular job boards that the prospective employers prefer to make their next hiring from. You need to have a well-maintained LinkedIn profile that will speak out for you. Other than these websites, networking, contacting your acquaintances might also present you with a suitable opportunity. Meanwhile, here’s the trend of job listings in the first half of 2019.

Why is it a Right Decision to Become a Data Scientist?

Two friends, Ross and John read that there is an increase in the competition and salary base is steady. Now, when they heard this, a question creeped in their mind- Is it the right decision that we have taken to become a data scientist? They were the freshers in the field. What do you think of these two friends? Are they doing the right thing by thinking about their decision, now when they have come so far after joining an online data science course and starting their studies?

There’s nothing wrong in this thought. Due to the presence of number of online data science certification courses, the total number of people entering this field is increasing. You can easily spot freshers, as compared to the experienced and skilled data scientist professionals.

Yet another reason that might have made Ross and John give a second thought to their decision is utter confusion. The job listings mix up data scientist role with every other role in the field. When the organizations say that they are hiring data scientists, chances are there that they might be hiring data analyst or any other professional. Staying clear about how does a data analyst differ from a data scientist and how are other roles different, is the need of the hour.

In a nutshell, Ross and John, being freshers, made the right decision. They just need to be aware of the nuances of the field and target entry level jobs in the beginning, instead of straightaway going for the top role- data scientist.

Influence of the Unparalleled Hype of Data Science

This is no secret that data science is here to stay, grow and become very big in the coming few years. It is not only empowering the businesses but also preparing the professionals for a potential stable career. While there might be many evidences to show and support this statement, there are instances to show that preparation to handle this unprecedented hype has started at all the levels. Here is an instance to prove this readiness.

According to a news piece in April 2019, the-cut off for the statistics courses has been increased to 90%. This is done in accordance with the sharp rise in the requirement for statisticians in data science.

With an intention to make you aware of the prevalent trends in the data science job market in the first half of 2019 and ease your job search, this article has all the key elements to keep you updated. While it is not that difficult to make a transition to this field or to a new job in this field, what is necessary is that you know the don’ts of this field.

Here is an example from LinkedIn about what you need to keep an eye on.