The data scientist role has been attracting quite a bit of attention and interest--but if you're considering a job in that field, make sure you know what you're taking on.
College students are enrolling in data science majors, and some are even changing their majors to data science because it's a growing and lucrative field. But data scientists are also a special breed. How do you know if you'll be happy in a data science career? These 10 clues may help you determine whether a data scientist role is right for you. If you decide yes, be sure to check out the career resources at the end of this article.
Check out this free ebook for a look at other IT job roles to help you decide if they're a good fit for you.
1. You don't like statistics
Data science is packed with statistical analysis. If statistics don't appeal to you, data science isn't a good fit.
2. You don't like to work for long periods of time alone
Data science can require extended periods of concentration. This work is best done alone and with minimal interruption. If you are a highly social person and desire constant interaction, a data science career might be too isolating.
SEE: Hiring kit: Data architect (Tech Pro Research)
3. You're not detail oriented
Attention to detail is important in data science, because you're working constantly with statistics, data, and the mathematical and logical algorithms you develop. Along with this work, you must be continuously analyzing outcomes of your work. An individual with a detail-oriented mind is the best fit for this activity.
SEE: How to build a successful data scientist career (free TechRepublic PDF)
4. You don't like tedious tasks
Up to 60% of data scientist time is consumed in data preparation, a tedious activity that involves standardizing data terms, cleaning up data so that it can be used, etc. There is nothing glamorous about this work, but if you don't do it, you won't have a good set of data to run your algorithms against. You should ask yourself if a job with as much as 60% of data preparation tedium will make you happy.
5. You don't have a strong technical or engineering background
A strong background in engineering, IT, statistics, and data modeling is important for data scientists. If you are coming from a background other than this, you might have difficulty doing the job.
6. You can't accept failure
Data science is experimental work. You're trying different algorithms against different combinations of data. Like most researchers, data scientists encounter many failures because not every algorithm or theory works. Great data scientists know when to quit and when to try another approach. When they fail, they try again. If you feel you might not have the resilience to accept repetitive failures, a data science job might not be for you.
SEE: Cheat sheet: How to become a data scientist (TechRepublic)
7. You like predictable work
Data science is anything but predictable! Sometimes unique insights can turn up from nowhere. In other cases, what you think was a good formula or algorithm to apply to the data yields nothing. A data scientist job is not for someone who likes coming to work each morning already understanding how their day is going to go.
8. You don't like desk work
If you like IT but also like to move around physically and take a break from your desk, a job in networks, telephony, or operations could be a better fit. Data scientists, because of the detailed nature of the work, spend long hours at their desks.
9. Data bores you
Being a data scientist is all about data! You have to clean data, put it together, process it, analyze it, and then do more of the same. It helps if you enjoy the challenges that come with working with data.
10. You don't understand how to translate business problems into data algorithms
If you're employed at a company, you'll need more than a degree in data science. Your internal customers will expect you to understand the business and--and the sticky business problems they want you to help them solve with data science. A skilled data scientist knows how to get at the core of a business problem and get to the right data. If you feel you lack this business savvy or instinct, a data science career might not be a good fit.
Does being a data scientist seem right for you? These resources can help
- How to become a data scientist: A cheat sheet (TechRepublic)
- 10 questions data scientists should ask employers during a job interview (TechRepublic)
- Data scientists really love their jobs, survey finds (ZDNet)
- The 10 most popular machine learning frameworks used by data scientists (TechRepublic)
- The 10 cities with the highest salaries for data scientists (TechRepublic)
- Hiring kit: Data architect (Tech Pro Research)
Are you thinking about embarking on a data science career? What pros and cons are you evaluating? Share your thoughts with fellow TechRepublic members.