If you’re reading this, then I’m going to bet that you want to be a data scientist. The job market is fierce and there are more people with degrees in statistics or computer science than there are jobs for them. But if you really want to make it into the world of data science—and make no mistake, this is a high growth area—then here’s what you need to know:
1. You’re an IT professional.
You’re an IT professional.
You’re the person who makes sure that your office has internet and printers, that everyone has access to their email accounts, and that the servers are running smoothly. You might be responsible for maintaining databases or keeping track of company files on a server somewhere in another state. Your job is to make sure things run smoothly so that business owners can focus on their core competencies: selling products and services, managing people and projects, creating new products or services (and more).
If you’re an IT professional, great! Your skills are valuable–and they’ll continue to be valuable as long as we have computers around us. But if you want more money than what most IT jobs pay these days (which isn’t much), then it might be time for a career change into something else entirely…
2. Your job is to manage data.
If you’re a data scientist, then your job is to manage the data. You may not be a programmer and don’t have any interest in becoming one. But if you are an IT professional and want to know if your skills are aligned with those of a true data scientist, ask yourself these questions:
- Do I have an understanding of how to store and organize large amounts of information?
- Do I know how to access that information quickly when needed?
- Can I create reports from this data that will help others make decisions based on it?
3. You have a degree in computer science, math, or statistics.
You may have a degree in computer science, math or statistics. You might even have a PhD in one of these fields. That’s great! But it’s not required to be a data scientist–and it doesn’t necessarily make you more qualified than someone who doesn’t have one of those degrees either.
Data scientists don’t need to know every aspect of their technology stack inside and out; they just need to understand how their tools fit together so that they can collect, analyze and interpret data effectively (and quickly).
4. You’ve worked in technology for some time and are at least familiar with the concept of data science.
If you’ve worked in technology for some time and are at least familiar with the concept of data science, then you may already have some of the skills needed to be a data scientist. Data scientists come from many different backgrounds, but most have experience working with large amounts of raw data and technology that can help them analyze it.
Data Science is a relatively new field and not all computer science majors will become good candidates for jobs as Data Scientists. However, if you have been working with databases or machine learning applications for several years now, then this might be an area worth exploring further!
5. You understand how to ask the right questions of your data and what kinds of answers will be useful from it.
Once you have the data, it’s important to know how to ask the right questions. You need to be able to understand what kind of answers will be useful from your analysis. For example, if you are looking at customer purchasing habits, do they buy more often when they use a coupon? Or do they buy less often when they use a coupon? This can help determine if offering coupons is actually profitable for your business or not.
A good data scientist knows how to frame these types of questions in order get answers that will help them make better decisions about their business (or whatever else their job entails).
6. You have experience with programming languages like Python or R, databases like MySQL, and other common tools for handling large datasets like Hadoop, Spark and so on… and can talk about them if asked about them casually at lunch or after work drinks!
You should be able to talk about the programming languages and databases you use.
You can talk about the tools you use to process data, like Hadoop or Spark.
You should be able to explain how you use data to solve problems at work, or even just in your life!
If none of these are true about you then you are probably not a data scientist
If none of these are true about you then you are probably not a data scientist. You may be an IT professional, or a software engineer, who has been tasked with building the infrastructure for a company’s data science team (or perhaps even leading that team). If this is the case then it’s important to understand what skillsets are required for your role and how they differ from those of an actual data scientist.
A good way to do this is by comparing your job description with those posted on job boards by companies that hire data scientists. For example data science salary:
- Are there any requirements related to programming languages? If so which ones? Does it matter what languages I know?
- Is there anything in here about being able to work with large datasets like Hadoop or Spark?
Conclusion
If you think about your job and how it fits into the bigger picture of data science, you’ll have a better idea of whether or not you’re in the right field. If none of these are true about you then you are probably not a data scientist!
