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Learn everything about Analytics Home Data Science 4 Secrets for a Future Ready Career in Data Science


Automation has impacted, and will continue impacting, jobs in many domains. Every single job on this planet is subject to a risk of job replacement by bots – just the intensity might differ. Automation makes running a business more efficient on one hand, and on the other, it keeps on changing the skill set required to stay relevant in the industry.

This inevitably leads to unemployment due to mismatches in the skill set. Let me take you through a few scenarios to illustrate my thoughts.

Scenario 1 – Manual Roles You are an HR professional in the year 2000, when most of the company employee documents were on paper. You are very efficient in sorting documents and retrieving them when needed and have been a star performer for more than 5 years because of these skills.

Given that the HR processes did not change much over time, you did not pick up computer skills over the next 18 years. However, the way industries work have changed a lot from 2000 to 2018, and now all the employee documentations are on the cloud or a private server.

So, your most sell-able skills are now suddenly not that important. You might face difficulties finding a job unless you upgrade yourself for today’s evolved industry. Note that your skill set mismatch was not because of the evolution of HR specific processes, but the dynamically changing business processes that you support.

Scenario 2 – The Preference of Customers You work as a news reader on the radio in the era when there was no television. You are very well informed about current affairs and hence you were a strong performer. But after television became mainstream, radios almost went out of business. Your radio employer had to let you go because they were sustaining heavy losses.

Now, given your skill set, you can still try to get a job as a TV news reader but you need to work on your body language and the crippling fear of facing the camera. The good news? You have been hanging out with people who work in the TV news industry and hence you know your opportunity areas and have been actively working on them.

Note that this time neither your profession evolved, nor your industry. It’s just that the customer started preferring an alternate product/service to the business you support, making your skill a mismatch (or obsolete) in the industry.

What did we Learn from these Scenarios?

In the scenarios above, we witnessed that the changes around us are making businesses easy to run but at the same time are  creating job skill mismatches, leading to unemployment in specific domains. Below are the three main reasons of job skill shifts in the industry:

It is no surprise that automation and changing business domains have disrupted many jobs. An important questions now is:

Will some jobs be impacted more than others?

Even though no one really knows what jobs will be more/less impacted by automation, here is a framework that helps understand the broad idea. Machines are not good at learning from too few examples and machines are not good at being creative. So if your job has these two attributes, you should be just fine. For instance, driving a car is a very repetitive process and does not involve a lot of creativity. Hence, cab drivers are at a high risk of their job facing automation. Is Data Scientist a Robot-Safe Profession?

In this ever-evolving AI-led world, we (data scientists) are definitely on the better side of the deal. Where does the role of a data scientist fall in the graph shown above? As a data scientist, we do a varied set of jobs to help businesses grow. Each of these jobs fall at a different place in the graph above. The below image shows my thoughts on the different sub-jobs we do as data scientists (proportion might vary with individual roles): As you can see,

Not all the parts of a data scientist’s job come with a 10 year warranty. Depending on your specific role and proportion of work that is difficult to automate, you can estimate your risk of automation.

Consider a data scientist in 2010. Key skill sets were knowing logistic and linear regression, and conversant with base SAS and MS Excel. Now, if we bring this data scientist of 2018 without any significant upgrades on tools and technique, he/she can face hard time finding data scientist job.  With good certainty it can be said that even though the data science stream will stay up and running for long term, the roles and responsibilities of these jobs are up for big changes. People who have challenges upgrading to these new roles and responsibilities will face strong setbacks in progressing in career.

Given the young workforce in data science field, skill set match is not a concern over short term as most of the people working in this field have recently picked up knowledge in latest tools and technique. However, as the field gets old so does the workforce and skill set mismatch within data science domain is definitely possible if this workforce is not able to upgrade their skill set while managing their daily jobs.

What can we do to make sure we stay productive and irreplaceable in the long run within the field of data science?

Four things I would recommend for data scientists in any kind of role to build a future proof profile:

With a high focus on data-driven strategies across domains, data scientists are kept busy with their job at hand. Not staying updated on each of the 4 pointers mentioned above can be dangerous in the long run.

To fill this gap in the industry, Analytics Vidhya has handcrafted a four day conference – DataHack Summit 2018. After the success of the Summit last year, we have further optimized the schedule to pack it with everything you need to know to come up to speed in terms of tools, technologies, and business domains.

Sounds too good an opportunity to pass up? Good! Tickets are almost sold on, so grab yours here TODAY!

How can you best use DataHack Summit 2018 to upgrade your knowledge on all the 4 key pointers? End Notes

Here are a few helpful links for DataHack Summit 2018:

We were overwhelmed by the response we got from the participants at DataHack Summit 2017. Let’s make DataHack Summit 2018 an even bigger success!

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