Data science is being talked about a great deal at the moment, it’s being used everywhere from huge multinational corporations to the government to internet startups. However, when people talk about data science they seem to spend a lot of time enthusing over it without actually going into the detail of what it means! So we’ll do that here. Read on to find out what data science is, what your job prospects are if you choose it as a career path, how you can train and importantly what it’s actually like to work as a data scientist.
What Is Data Science?
Data science means gathering huge amounts of data, analyzing it, and then using that analysis to predict trends. A data scientist needs to know how to gather the relevant data, store and organize it in such a way that it can be easily worked with later, and they need to be able to develop models and apply problem solving to predict trends.
A lot of data that data scientists are working with relates to human behavior. They will collect data on how a particular group of humans is behaving, for example what products they are buying or not buying, what they are searching for online or even what events and gatherings they are attending. This data is then cross-referenced with other relevant data - -for example, the time of year, the age group of the data set, or any global situations like the coronavirus pandemic. From this the data scientist can create models to predict how humans are likely to behave under the same or similar circumstances in future. They will then make predictions based on their results as to how humans are likely to behave in the future, which can inform decisions such as which products to develop, how to market them or even how to approach mitigation of a pandemic.
According to the BLS (Bureau of Labor Statistics) employment of data scientists is set to grow fifteen percent between 2019 and 2029, which is a faster rate of growth than other fields. This essentially means that there are likely to be a lot more positions opening up for data scientists than in other areas, so training as a data scientist could be a good move as you shouldn’t have too much difficulty finding work.
The mean salary for a data scientist is $100,560 per year. The median salary across all workers in 2019 was $39,810, so it’s definitely a well remunerated profession! Companies from a multitude of sectors, both public and private, are starting to see the value in making data informed decisions so it's a career that could see you working in any number of different areas. At the moment the highest concentration of data scientists are employed in California, as you might expect, closely followed by Illinois and Texas.
Generally to work as a data scientist you will need a masters degree. Data scientists are trusted to provide accurate information that informs company direction and decisions, so employers want to be sure that you are qualified before letting you loose on their data!
You will need to be able to prove that you are adept at mathematics, statistics and computer programming. It also wouldn’t hurt to show that you have a good working knowledge of machine learning and artificial intelligence as this is the route that a lot of companies are starting to go down.
The good news is that a lot of data science masters programs covering all of the core skills that you will need are now available for online study, so you can start training for your new career without having to relocate for college and you will be able to keep earning too.
Data scientists can be employed in a number of fields, as we will go on to discuss, so it’s worth thinking about which field you would like to to work in and speak with your course convener about choosing appropriate modules for that field. It is also a good idea to reach out to people already working in your chosen field, partly to make contacts and show initiative, but also to get advice from them about how they got into their careers. An employer will want you to show knowledge about their business and the challenges it faces, so research is key.
A Day In The Life
Data scientists will commonly work standard office hours, around forty hours per week. Companies are increasingly becoming supportive of remote working, so if that’s something that works well for you it’s definitely worth requesting. You will probably have to go into the office sometimes, but a lot of employers will be supportive of you working quietly at home.
The actual daily life of a data scientist will vary depending on where they are employed, but in general there are a few common themes:
You will often be working on several projects at once, so learning to multitask (or more accurately to switch between tasks effectively - nobody actually works on more than one thing at once!) is key.
You will spend a lot of time working on data collection and analysis certainly, but it is also important for a data scientist to build relationships in the workplace. After all, nobody is going to take your suggestions if they don’t trust you. There will likely be a certain amount of meetings and on occasion you will need to present your findings to board members or other members of staff. Data scientists generally work in a team, working together to collect the data, build models and analyze it effectively. Teamwork is important because it allows you to develop your ideas by discussing them with colleagues.
Where Could You Work?
Really you could work anywhere! In 2019 the highest concentration of data scientists were employed in companies specializing in computer systems design. This sort of work will involve analysing what the current requirements of the computer system are, as well as predicting what the future requirements are likely to be so that these can be catered for when the system is built.
Data scientists are increasingly getting involved in Artificial Intelligence and Machine Learning projects too, using their ability to model and predict human reactions and behavior to design AI systems that can respond in the same way that a human would. This is being used a great deal in the medical field, with AI being used to model what the diagnoses of hundreds of doctors with varying backgrounds and experience would be and how they would proceed with treatment. This essentially means that having the AI system look at the patient is the same as having them in a room with hundreds of doctors (only without all the shoving) so that diagnoses and treatment can be more effective.
A current example of the uses of data science are in relation to the coronavirus pandemic. Scientists have been collecting data on where the disease has been the most highly concentrated, as well as modelling the behavior of the people in those areas. This allows them to create informed solutions and plans to mitigate further spread of the virus.
Data science is being used increasingly across multiple sectors, all you need to do is choose which one is right for you!