Data scientist is the hottest career of the 21st century. Nearly every successful company has a data scientist, who crunches data and finds solutions to their pressing challenges. These professionals are handsomely paid. In fact, one of the highest in the world. So what are data scientist, what they do, and how they do it. Let’s find out below.
What does a data scientist do?
Data scientists solve problems using data. Data science is a multi-disciplinary field which uses knowledge of mathematics, computer science, and statistics. They work at the intersection of business and technology – where technology solves business problems. So they require understanding of both. A data scientist collects, analyzes, and interprets data to figure out solutions to problems that a business is facing. Data science gives a competitive edge to companies.
How to become a data scientist?
The current data scientists have followed a sporadic path to be where they are today. However, the industry and academia now offers straight path to become a data scientist. Here are a few options.
- Earn a bachelor’s degree – The demand for data science professionals has increased significantly over the last few years. Other closely related roles like data analyst, data visualizer, machine learning engineer, etc. are equally in demand. Though earlier undergraduate courses didn’t exist for data science, now they do. University of California, Irvine; Yale University; University of Rochester; Columbia University are a few universities that offer bachelor’s degree in data science.
Get an entry –level job – If you’re past the bachelor’s degree phase, you can try getting an entry –level job that is closely related to data science. You want to work as a data scientist. However, without requisite knowledge and experience, you’re less likely to get a data scientists job. Companies look for extensive data crunching experience, whole hiring for data scientist’s role.
Getting a job that is closely –related to data science – data analyst, business intelligence expert, database management, among will help to eventually climb to the data scientist’s position. This will require 3-6 months of preparation, for which you can opt for short –duration data science certifications and courses.
3. Take a master’s degree or Ph.D in data science
Data scientists armed with master’s or Ph.D degree are in high demand. In fact, master’s degree and Ph.D holder’s in data science are the first choice for companies that are looking to hire a data scientist. You can choose a concentration in mathematics, statistics, or computer science.
4. Get a promotion – If you’re in in data science –related role, you can upskill yourself and look for promotion. You also have the opportunity to switch and take a higher position than the current one.
What skills do you need to become a data scientist?
A data scientist needs a plethora of skills, which varies from hard skills like strong quantitative aptitude to soft skills like communication skills. The following are the skills that you need to learn to become an excellent data scientist.
- Good analytical skills – Data scientists are expected to look at problems from an analytical view. Further, they use analytical approach to dissect a problem and find patterns (if any), to solve the problem.
- Communication skills – Data scientists work with business leaders, C-suite executives, and managers to understand a business problem or processes and eventually find a solution. A single process has multiple stakeholders. If a problem is found or any patterns are seen, data scientists are expected to communicate their findings to all stakeholders in the clearest approach possible. This requires data scientists to have good communication skills. Being able to express ideas, findings, and solution to stakeholders is a crucial skill to excel in a data scientist role.
While you can learn technical skills from data science certifications and courses; if you’re weak at expressing yourself, improving your communication should be a priority. - Critical and logical thinking skills — Being able to spot patterns in a pile of data is as important as being able to see the logic behind such patterns. Data science is a complex field, so good reasoning skills and critical thinking is important to thrive in this role.
- Mathematics skills – Statistics and mathematics are the foundation of data science. So it’s no wonder that aspiring data science professionals stress on these skills. If you’re starting out, mastering statistics and mathematics skills should be a priority. The better you’re at maths and statistics, the better data scientist you can become.
- Programming and tools – R, Python, SAS, and SQL are pre-requisites for becoming a data scientist. If you’ve a background in computer science, it will be easier to learn these skills. Alternately, you can take data science certifications and courses to become proficient in these skills.
Ingenuity – The reason companies employ data scientists – companies sometimes don’t know if they’re facing a problem. Data scientists find out such problems and if companies don’t know that a problem exists they can’t find a solution. Data scientists have to sometimes think out of the box to find a problem as well as find a solution. Data science is still a new business function; professionals don’t always have solution especially for unanticipated ones.
