Before we get into the details of a Data Scientist. I think it’s only fair if we explore a bit more about the field of a data scientist.

Right?

With that, let’s start with this.

What the heck is Data Science?

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 bit more and I’ll see if the next topic help you.

Who are they?

Data Scientist is a type of profession.

Well, as the name would imply, they are somewhat similar to a scientist except that they tend to work closely with data and statistics.

All the data that they work with could vary from small to large and from simple to complex. You name it.

Data Scientist could be found in most of the modern company, as they need them to work with all the numbers, statistics and make use of it to solve problems and make improvements after the interpretation of the data.

What are their job and tasks?

As mentioned earlier, Data Scientist is in the field where they have to collect complex and large amount of data. And this can be from various sources depending on their target, analyze them and come out with the best solutions.

For example, data analyst of an automobile company has to collect data regarding consumers spending behavior, and the best way to increase their performance.

As a data scientist, they have to find the best method to collect, read, and interprets the data by using the suitable techniques and tools such as programming and even machine learning and A.I. to aid them in accomplishing their tasks.

Why do we need a Data Scientist?

Data Scientist does not just collect and analyze data, they also have to utilize the data that they collected.

In short, company and organizations need them to solve problems and make improvement but it is not as simple as it sounds.  As they collect and interpret all the data, they will need to make decisions based on it to grow the business day by day. For example, before emerging to a new area of investment they need to analyze its suitability in terms of riskiness and profitability.

Where do Data Scientist work?

As a data scientist, they could work anywhere as long as they have the tools that they need to perform their tasks. However, it is varied for different employer. Working at home, office or even in a café it does not really matter, as most of the time you are working with all the data and maybe your team.

In addition, data scientist need to be responsible as the data results that they interprets could be used to make crucial decisions that will affect the company drastically in the future.

Who does Data Scientist work with?

Except from dealing with data and statics, most data scientist work with their team and other departments in a company especially those related to strategies and data sensitive. Since the results are important for making decisions, they too have to hold meeting on reporting and making any decisions for the company.

Future of Data Scientist

As machine learning and A.I. began to rise rapidly in these recent years, people who are working as a data scientist and who wanted to become one are concerned that will this particular career be sustainable, are they going to be replace anytime soon in the future.

The answer is no.

As there are still a lot more to be discover and its capabilities to accomplish new goals. Data scientist only became popular in the year of 2010 and instead of being replaced by machines or A.I., they will be working together to accomplish bigger goals and create better performance out of it.

Demand for Data Scientist

Furthermore, as businesses becoming more competitive, the one who are not utilizing data will execute from the market. These data scientist will try to build better solutions than competitor to help interpret data more efficiently and effectively, that would help the company to make a reliable, accurate and eventually increase their overall performance.

With the aid of automation and A.I. the data could be interpret efficiently but they could not understand the true meaning of the results. It is not only about analyzing data but also solving problems and make improvement, A.I. have yet the ability to make a reliable decisions as there are more than just data do be considered. Unlike human they does not have emotions, therefore data scientist are still needed to perform tasks that machines could not.

Besides on what A.I. or machines cannot perform, the least requirement to become a data scientist will also be higher in the future, where the tasks and roles will be much complex.

Last but not least, the growth of machine learning, A.I. data and all industry will drastically increase the demand of data scientist. So watch out for that space.

Note 2: If you’re interested to know more. I also wrote an article on getting paid more as a Data Scientist (click here). Enjoy!