Interested in landing a job as a data scientist? Now’s a great time to choose a career in data science—Glassdoor has once again named Data Scientist the #1 best job in America. But how do you get your foot in the door, and what does it take to succeed?
What IS Data Science?
Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science. This can be daunting if you’re new to data science, but keep in mind that different roles and companies will emphasize some skills over others, so you don’t have to be an expert at everything.
Pro tip: “Data scientist” is often used as a blanket title to describe jobs that are drastically different!
Reading Data Science Job Descriptions
One important piece of advice for your job search is to read data science job descriptions carefully. This will enable you to apply to jobs you’re already qualified for, or develop specific data skill sets to match the roles you want to pursue. “Data scientist” is often used as a blanket title to describe jobs that are drastically different. Let’s looks at four kind of data science jobs.
4 Types of Data Science Jobs
1. The Data Analyst
There are some companies where being a data scientist is synonymous with being a data analyst. Your job might consist of tasks like pulling data out of SQL databases, becoming an Excel or Tableau master, and producing basic data visualizations and reporting dashboards. You may on occasion analyze the results of an A/B test or take the lead on your company’s Google Analytics account.
“A company like this is a great place for an aspiring data scientist to learn the ropes.”
Once you have a handle on your day-to-day responsibilities, a company like this can be a great environment to try new things and expand your skillset.
2. The Data Engineer
Some companies get to the point where they have a lot of traffic (and an increasingly large amount of data), and they start looking for someone to set up a lot of the data infrastructure that the company will need moving forward. They’re also looking for someone to provide analysis. You’ll see job postings listed under both “Data Scientist” and “Data Engineer” for this type of position. Since you’d be (one of) the first data hires, heavy statistics and machine learning expertise is less important than strong software engineering skills.
“Mentorship opportunities for junior data scientists can be less plentiful at a company looking to leverage rapidly increasing amounts of data.”
As a result, you’ll have great opportunities to shine and grow via trial by fire, but there will be less guidance and you may face a greater risk of flopping or stagnating.
3. The Machine Learning Engineer
There are a number of companies for whom their data (or their data analysis platform) is their product. In this case, the data analysis or machine learning going on can be pretty intense. This is probably the ideal situation for someone who has a formal mathematics, statistics, or physics background and is hoping to continue down a more academic path.
“Machine Learning Engineers often focus more on producing great data-driven products than they do answering operational questions for a company.”
Companies that fall into this group could be consumer-facing companies with massive amounts of data or companies that are offering a data-based service.
4. The Data Science Generalist
A lot of companies are looking for a generalist to join an established team of other data scientists. The company you’re interviewing for cares about data but probably isn’t a data company. It’s equally important that you can perform analysis, touch production code, visualize data, etc.
“Some of the most important ‘data generalist’ skills are familiarity with tools designed for ‘big data,’ and experience with messy, ‘real-life’ datasets.”
Generally, these companies are either looking for generalists or they’re looking to fill a specific niche where they feel their team is lacking, such as data visualization or machine learning.
You May Be More Qualified Than You Think!
Hopefully this gives you a sense of just how broad the title “data scientist” is. Different companies are seeking different skillsets, expertise, and experience levels. As you look for your ideal data scientist job, make sure to look closely at the job descriptions, to find the role and company that best match your skills and experience. And remember, you may be more qualified than you think!
What next? Focus on the skills that matter
Each of these types of data scientists have different skills that matter most. The picture below gives some insight and see our post on data scientist skills to learn more!
No matter what skills you possess or how much experience you have, Udacity has the perfect data program for you, to ensure you learn the skills you’ll need, to build a career you’ll love!