Get Paid (More) Working in Data Science?

Reading this now, you must be really curious about the topic. OR you have already read about Data Science and probably want to get a job in this area. And if you’re already working in this role, you want to get a pay increment for being in this area.

I’m sure you’re interested in one or all of the above, and I hope I can share some of my own perspective of this area so that you genuinely find a way to make this a fulfilling job.

What is heck is Data Science?

Before we get our hands dirty, and just so that we’re on the same page, let’s clear the air on some of the areas that I’m about to cover.

What is Data Science? And what does it mean to me (Alwin)?

Well, let’s start with some simple definition:

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data.”

Well, this happened to be the same definition taken from Wikipedia. However, in Wiki, it also continues to state:

Data science is a “concept to unify statistics, data analysis, machine learning and their related methods” in order to “understand and analyze actual phenomena” with data.

So there you go.

Now, in case some of you still does not have any clue what this is about, don’t worry. I was completely confused with the long explanation as well. So let me try to put it in a few simpler words. In short, all it’s trying to say is:

Data Science is the science of how you can get USEFUL INFORMATION out of a mountain of data and MAKE SENSE of it.

Get it? I hope you do by now.

If not, just hang in there a tide more and I’ll see if the next topic help you.

So how do I get Paid (More)?

Now that we’ve put Data Science in words, let’s move back to the main topic of today – how do you get paid or get paid more for working in Data Science?

The truth is, this really depends on the organisation that you’re working for. Having said that, let’s assume that you’re working for a For Profit Organisation (which is means the objective of the organisation is to make money), then the answer might be a simpler one.

If you really want to be paid, then ask this:

How can I help the organisation make more money through the use of Data?

If you are already working for an organisation or you plan to join a specific organisation, it might be a good time to pause for a few minutes and have think about this.

 

 

(Pause now and continue from here once you are ready)

 

 

Now some of you might have a rough idea already and some of you might still be clueless. So let’s go a little a deeper on this topic.

It’s All About Performance (and Money)

You see, many people that I’ve spoken to (who are interested in Data Science) have probably done a wee bit of homework on data science and how data science can help an organisation. However, some still seem to feel lost because they can’t figure out how to do this work and get paid (or get paid more).

Apart from the fact that it does sound like a sexy job title, what can you focus on?

Many are confused and I’m not entirely surprise. And that’s probably because, many don’t really think enough about Data Science from a business perspective. They see it as just an activity or a task that comes as part of the job.

Let’s take another point from Wikipedia:

In 2012, when Harvard Business Review called it “The Sexiest Job of the 21st Century”, the term “data science” became a buzzword. It is now often used interchangeably with earlier concepts like business analytics, business intelligence, predictive modeling, and statistics.

Business analytics and business intelligence are areas that has it’s primary focus on business performance for many many years. These division within the business that tries to figure out how to improve the efficiency and effectiveness of business activities in the hope of increasing business profits.

Make sense?

I hope it does. Because, that’s the key to getting paid or getting paid more. You need to find ways to make more money for the company so that they can pay you more.

Not rocket science, right?

However, sadly, some students, employees or employees-to-be have failed to see this key point.

Data Science is Huge even though it’s NOT NEW!!

(Ok, I’m going to side track a little but I think this is an interesting information. So bare with me on this)

Yes, I said it and I’ll say it again. Data Science is not new.

In fact, in the financial sector (where I use to work), Management Information System (MIS) analyst and business analyst are common job titles. These people help the company analyse chunk and chunk of data, consolidate them and make them into pretty charts and reports that are sent for management review. Many multi national companies and organisations operate the same way too.

Having said that, as technology continues to advance, new areas like artificial intelligence (AI) and machine learning are emerging. These new technology will eventually take over the tasks of the analyst. Because of that, the role of the analyst will now evolve to become more performance review focus – as opposed to just data crunching.

For them, data science has been there and will continue to remain as an important part of large organisations.

It’s becoming Hotter for SMEs

Now, the story for small to medium size organisations is quite different. In fact, many smaller organisations are now starting to seek number crunching candidates to join their organisation. Data Science, even though is a bit slower in making its entry, will eventually become a core part of their business too.

But why not earlier?

You see, while the need to data science is obvious in large organisation is common, that is only possible because there have ERP systems and databases that stores data. This is not really required by small organisations (in the past) mainly because many of them did not have ERP systems (or equivalent) as well as having access to business data.

With the rise of the cloud technology and the lower cost of entry, a whole lot more opportunities (for Data Science) are opening up in the SME market.

Revenue & Cost

Coming back to the idea of getting paid and getting paid more, the next thing you need to work on is to be clear with your role and your services to your current/future company.

As mentioned, it’s all about using data to improve the performance of the business.

So that next question you should ask is, which area will you be looking?

For those who are not familiar with running a business, here’s a very quick video on Business Model Canvas. Don’t worry too much if you still don’t understand much of business canvas, the video gives a short and sweet illustration of the structure and the different parts of an organisation which is applicable to most organisations.

Enjoy!

Now, assuming you’ve watched the video, you should have noticed all the various types of activities pretty much get re-directed back to Revenue and Cost.

Of course is does.

Essentially, all businesses or organisations (assuming that’s where you choose to work) aims to increase profit. And the simple equation that you MUST know is this:

PROFIT = REVENUE – COST

If you are going to be doing work in data science, for ANY organisation, and if you can help increase Revenue or reduce Cost, you will definitely get paid or get paid more.

Having said that, if you are working for a smaller organisation, make sure to ask your employer which is more important. Some prioritizes revenue over cost and some prioritizes both. Don’t assume, so go check before you go deep dive into your work.

Get the direction right, and you’ll be paid handsomely.

Conclusion

Data Science is an important area in business and this will be an even more important area as organisations continues to grow. The fuel that will push the rise of this work scope is also driven by the lower cost of technology.

Hence, if you can show, through the use of data and data science, how you can help an organisation increase profit, I assure you that you’ll be rewarded 9 out of 10 times.

Note: If the company does not appreciate data and prefers to run the business with his emotions, then you should consider changing jobs IF (and that’s a very big if) data science is your true calling. Just to be clear, that’s just my opinion. Get more feedback before taking any action. 

Thank you for reading and feel free to post any questions that you may have below.