The Most Overlooked Skill for Data Science Job Applicants in 2019

The Most Overlooked Skill for Data Science Job Applicants in 2019Ken JeeBlockedUnblockFollowFollowingJul 4Data science positions saw a 56% increase in openings over the past year.

There is huge demand for talented labor to fill these roles.

Forums explode with threads about the best language or framework for the industry.

However, no single algorithm, language, or insight will get most people hired.

What will get you a job is a decent technical background and strong subject area expertise.

photo credit: David KovalenkoWhat is subject area expertise?In my opinion, subject area expertise falls into two categories: Industry specific knowledge and data science specific knowledge.

If you are able to master one or both of these, you are likely to set yourself up for success in the job market.

Industry expertise — mastery of the work domain of the role you are applying for.

For my work in sports analytics, I have found this particularly useful.

If an applicant has a wealth of sports specific knowledge, they are better able brainstorm project ideas, can find common sense faults in their work, and are able piggyback on other research that has already been done by themselves or others in the field.

I have also found that these candidates have unique personal projects that can provide immediate value to my clients.

Hiring them is also purchasing their existing work in a sense.

Obviously, this has to be acceptable by their standards as well.

Data science specific knowledge — in-depth understanding of a type of analysis in which a company wants to expand their capabilities.

For many companies, it is far easier to hire an expert in a certain area than to train someone to learn a skill-set.

If you have put in significant work on NLP or computer vision projects, this could set you apart in roles requiring these specific skills.

Personally, I have developed a broader skill-set, but I believe that I could have definitely improved my chances if I had really honed in on one area.

Why subject area expertise?Often times, companies are looking for data scientists to fill a specific role or to handle a specific task.

For many businesses, a lead scoring model or an image classification algorithm encompasses the majority of the data science work that they do.

Hiring managers will be looking for someone with a specific data science skill expertise to fill this role.

On the other hand, if you have industry area expertise, you become significantly more appealing to a company hiring a generalist.

If you are already familiar with the basics of the industry, you can spend the majority of your time working on various different data science projects.

You can also help with project ideation, planning, and prioritization.

If you have some elements of both data science skill and industry specialization, you give yourself tremendous flexibility.

You can either work on a single large project within a company, or you can capitalize on your breadth of knowledge by working on many projects.

How to gain subject are expertise?Like any skill, subject area expertise can be acquired.

It is of my personal belief that you do not have to gain these skills directly from previous employment.

I highly recommend working on projects in your own free time to develop these two types of expertise.

I always recommend kaggle.

com or reddit for data and background on these projects.

These places have great communities where you can engage with people that can help you to build this knowledge.

It is also practical to seek out mentors in these areas.

You can easily trade data science skills for industry expertise.

With mentorship, I always believe in bringing something to the table.

For example, if I was interested in learning more about healthcare, I would find someone through my network who is advanced in that field.

I would offer my insights about how tech might influence their work in exchange for their advice and knowledge.

I would recommend trying not to make this transactional, but still make it clear that you can provide some value to them.

In terms of technical expertise, I believe that there is a tremendous amount of high quality educational material out there.

But what if I get pigeon-holed?A reality of specialization is that you will likely work in one specific field or in a singular industry.

Some might see this as a bad thing.

I would argue that learning how to specialize makes it easier to specialize in something else down the road.

There is a level of intricacy that you discover in each field.

If you are looking to transition to a new position, you can start the same process over again.

There are many people that specialize in multiple different things.

For example, my background started in the golf industry.

I was able to also gain a solid understanding of predictive models and Monte Carlo simulation.

With this understanding I was able to eventually learn how to apply my work to other sports.

When you specialize, you capitalize.

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