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Data Scientist has been called the Sexiest Job of the 21st Century... but many people (including some companies trying to hire data scientists) don't really understand what this job means. The term is used to describe a wide variety of roles; A data scientist at one company doesn't necessarily do the same thing as a data scientist at another company.

Below I break down some of the different 'types' of data scientist jobs there are and the skills needed for these various roles. Please note that this list is not exhaustive, and sometimes a data science position expects someone to fill multiple of the below roles:

Data Analyst

Derive business insight from data.
Work across all teams within an organization.
Answer questions using analysis of data.
Design and perform experiments and tests.
Create forecasts and models.
Prioritize which questions and analyses are actionable and valuable.
Help teams/executives make data-driven decisions.
Communicate results across the company to technical and non-technical people.

Required Skills: SQL, Statistics, programming, data management, data analysis, data modeling, data visualization, experimental design, decision making, prioritization, project management, product development, communication.

Data Architect

Design systems to get raw data into an easily analyzable form.
Act as a bridge between engineers and analysts.
Organize data into useful database tables for analysis.
Optimize data sets for efficient analysis.
Create ETL Systems for your data sets.

Required Skills: SQL, computer programming, backend software engineering, database design, database management, data optimization, data modeling.

Data Engineer

Work with analysts to build internal tools for analyzing, visualizing, and sharing data.
Design and maintain A/B testing systems.
Work with engineers to insure that the right data is being collected.
Create systems which allow analyst work to scale.
Work with data architects / operations to insure the data is organized for optimal analysis.

Required Skills: SQL, computer programming, full-stack software engineering, data visualization, database management, communication.

Domain Experts

People who have advanced specializations like:

Machine Learning
Natural Language Processing
Algorithms
Financial/Economic Models
Graph Theory
Supply Chain Analysis
Operations Analysis

Required Skills: Advanced degree in computer science, math, statistics, finance, or economics. Programming, statistics, data management, data analysis, data modeling, data visualization, experimental design, communication.

Unicorn
Someone who does all of the above.
(basically impossible to find, thus the name)

Some FAQs about Data Science Jobs

Q: Do I need an advanced degree to be a data scientist?
A: No
In general, the tech industry cares very little about degrees or pedigree. I have been at companies where the CTO didn't graduate high school, and I have been at companies where many people have PhDs. I would be very surprised if any company would not consider an (otherwise qualified) candidate for a data role just because they didn't have a certain degree.

That being said, many of the skills required to be a data scientist overlap with the skills required to be a scientific researcher. People who have worked as researchers (either because they did an advanced degree, or because they worked in a lab) tend to be good candidates for data science jobs.

However, you can get this experience in a lot of other ways. For instance, many people start out as (junior) analysts where they pick up many of the skills needed to be data scientists and then become data scientists after 3-5 years of industry experience. Some people start out as software developers and work on more and more data-oriented projects and get into data science through engineering. Other people start out as financial, marketing, or business analysts and become data scientists through that path.

If you want to be a data scientist, I would look at the skills required for the above roles and then find ways to develop those skills either through schooling, your current job, or self-directed projects.

Q: What are the most important skills needed to be a data scientist?
A: SQL, Data Analysis, Programming
Of course, this depends on exactly what is expected for a particular role. Some data science roles are more analyst-oriented, some are more engineering-oriented, some are more specialized. This is something you can assess from the job description, but should also be discussed during the interview process.

However, in general I would say the most important skills are the following:
1) SQL
2) Data Analysis
3) Statistical Programming

So if you were going to learn one thing, I would say learn SQL. Then do a project that involves analyzing a data set and deriving results. Then learn a programming language like Python or R.

Q: How do I develop these skills?
A: Online course, hackathons, meet-ups, volunteer organizations.
There are a lot of great online resources which can help you develop these skills.

Coursera, Khan Academy, and MOOCs through various universities all have free online data science courses.
My friends at Mode Analytics have an awesome SQL school where you can learn SQL.
You can get involved with hackathons or other meet-ups where you can develop your programming and software development skills.
You can participate in a Kaggle competition, or go through some of the previous Kaggle data exercises.
You can get involved with organizations like DataKind, Data for Good, or Bayes Impact which all do data projects with social impact.

People reach out to me a lot asking how I got into data science and wanting advice about breaking into the field. Fortunately this is something I have written and talked about quite a bit!

Below is a compilation of the various things I have "out there" about my transition from academia to data scientist and what it's like to be a data scientist:

What is a Data Scientist? - General overview the answers to some frequently asked questions.

Transitioning Advice / Information
Astronomer to Data Scientist - Advice on how to make the transition from academia to data scientist.
Astronomer to Data Scientist (Talk) - More advice, and some details about what I do for my job.
Astronomy vs. Data Science - Compares and contrasts academia and the tech industry.
Nailing the Data Science Interview - Advice for preparing for your interview and what to expect.
Astronomy to Data Science, Three Years Later - An update on my transition.
Interviews
Interview with Lady Paragons - What my job is like, what I do, some other stuff too.
Podcast with Lady Paragons - More about what it is like to be a data scientist.
Interview with AAS on Women in Astronomy - More about my transition and what my job it like.

Recruiting Advice
Interview with HP - Advice on Where to Find Data Scientists:

Do you have more questions? Ask them below!