Companies can’t be competitive or even function in today’s market without data.
They rely on a healthy and daily stream of data, updated in real-time, to understand how their customers work, to be the first to know when trends start to shift, or to learn about the ways they could improve their product/service to make it more palatable to the market.
The answer to all their questions is hidden in huge amounts of data that come pouring in through platforms such as Google Analytics or business intelligence tools. But, to understand what’s going on, the data must be analysed, and this is a job for a data scientist.
In fact, this is one of the most sought-after types of specialist, so if you are good at it, you have all the chances in the world of becoming a highly-valued employee or entrepreneur. However, the term ‘data science’ is more of a buzzword, as it covers a wide array of specialities, and only a few people know its true meaning.
So, before you jump on this exciting career idea, let’s first have a look at what it entails.
What does a data scientist do?
As the name says, these guys are trained to decode large volumes of data, find patterns (or trends) and formulate an analysis that’s easy to understand by people who are not data specialists.
Data scientists have a cocktail of knowledge in fields such as mathematics, computer scientists, and logical thinking, but they also need to know the market for which they analyse the data. Furthermore, given the dynamic of the field, they are constantly learning and updating their knowledge toolkit to stay accurate.
The job of a data scientist is threefold, as they need to know:
- Where the information comes from (to assess its quality and reliability)
- What the data represents (the market it is going to be used into)
- How to turn raw data into a valuable resource for the company so it can be applied in various strategies (analyse and identify useful patterns)
Since big data is becoming more and more prevalent in the world of business, a data scientist has the freedom of choosing the industry in which they want to activate. The world can be your oyster in this position because data is used in industries like finance, manufacturing, communication, retail, sports, healthcare, and more.
Do I have the skills?
The most important skill a data scientist can possess is critical thinking. You’ll also need to be able to communicate complex patterns into easy to understand formats and an affinity for problem-solving.
Besides these, a data scientist must be able to work with statistics, machine learning, analysis tools, and some programming languages such as Python, file systems like Hadoop, and database processors such as SQL (to name a few of the tools you’ll be using).
The good news is that, if you like the field and feel you have the necessary type of thinking, there are lots of resources (free and paid) available to help you get an education. The even better news is that, once you’ve completed your education, you have high chances of getting a job as a beginner in data science and have the company help you continue the training.
Data science roles
We already mentioned that the term covers a large array of positions, so here are some of the most popular ones in the field:
- Business intelligence analyst – figure out trends in the market to understand the position of the company in comparison to the competition and in front of customers and partners.
- Data mining engineer – in this role, you will have to dig deeper into the data sets you’re processing and create algorithms that refine the results to a finer level.
- Data architect – you’ll be building database systems that take the data, store it, integrate it, and maintain it according to the company’s needs. Basically, you will work with a team within the company to understand the needs of the database, the data that is available and create a blueprint for how the data will be brought towards the company.
- Data scientist – this role combines the skills and tools of the BI Analyst and Data Mining Engineer. As a data scientist, you will need to be able to explain the effect of the trends you’ve identified on the company’s future and devise solutions to move forward according to what the data is saying.
- Senior data scientist – besides the roles mentioned above, a senior in this position has the experience to resolve highly complex business problems and create new standards and tools that use the analysed data in new and ingenious ways.
It’s important to keep in mind that we used a summary description of these roles, to give you an idea of what they entail. For more information, we strongly recommend conducting deeper research into the field.
If you’re still on the fence about getting into this industry, you should know that the average base pay for a data scientist is around 100,000 per year, and the beginner positions can start at around 60,000+ per year (source Glassdoor).
Furthermore, this position provides skilled people with job security and flexibility since it’s easier to change companies and even industries. Data science is a field that’s only going to get bigger, so if you are looking for a good job in IT, this may be the right answer.
Why did you choose data science as your career? Let us know in the comments below.