Nearly everything you do generates data. Visit a website: Data. Tap an app on your phone: Data. Buy something with a credit card: Data. Like or upload a picture on social media: Data. Billions of people are generating immense amounts of data every single moment of every single day.

That’s some big data, and it’s only getting bigger. Imagine what can be done with all that information--data scientists are doing exactly that. Data science is essentially the art of solving problems with data. You might have trillions of rows of data, but on its own that information means nothing. It takes work and specialized skills to transform it from unintelligible noise into something that can be easily understood.

Woven into all this data is information that can improve quality of life, identify societal issues, and address global crises. Now more than ever the significant advancements that can result from data are essential to find--it’s no surprise that being able to understand, analyze, and interpret data is a highly desirable skill.


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What do Data Scientists actually do?

Let’s get started by breaking down two of the most commonly asked questions––what is data science, and what are the responsibilities of a data scientist?

Data science is all about diving into a well of information and shaping it into a tool that you can use to accomplish a goal. Data scientists process data so it’s human-readable, building visualizations that tell a story or models that explain a process or predict behavior. Other times experiments are run to validate hypotheses in an attempt to prove them. The essence is that the raw data is used to output something that is valuable in that you can do or learn something with it.

Data Science job titles include:

How much are Data Scientists making?

Annual salaries range from $92k to $138k, and as of Apr 1, 2020, the average annual pay for a Data Scientist in the United States is $119,130 a year according to ZipRecruiter. This is one of the most lucrative high-paying careers in the tech industry today.

In a recent long-term outcomes analysis, Thinkful Data Science graduates showed that before Thinkful, students were earning an average of $53k, and after Thinkful, jumped up to $77k in their first job. Furthermore, after at least one year in the field, alumni were making an average of $101k. Check out our long-term student success outcomes for more information.

What skills do Data Scientists need?

This rapidly expanding field is tackling some of the biggest problems in the world today. But what does it take to actually be a data scientist?

Before you even begin learning the technical skills to get you into the industry, focus on the soft skills you likely already possess. These are integral to landing your next career as a data scientist:

Get in-depth advice on how to lean into these skills to kick start your confidence when switching careers.

Technical skills that are essential to get the job done, perform at a high-level, and meet career goals include:

Data science is rarely cut and dry. It isn’t simply "apply this technique" or "run this program". While necessary, that's usually the easy part. You need a thorough understanding of the problem so that you can determine which tools are best suited to your task. One of the most important skills for a data scientist is the ability to find solvable problems. Learning data science, then, is not merely combining programming with statistics — it includes that, but also requires context. You need to understand the domain that you’re working in, so you can test your hypotheses in the real world.

Hear from Data Science Mentor, Thanasis Paraskevas, on why SQL is such a powerful programming language, and how you’ll use it as a data scientist.With over 10 years of using SQL in a professional setting, his expert advice can help give you a glimpse into the process of learning and applying SQL.

How do I become a Data Scientist?

Learning anything requires a positive feedback loop. In designing our bootcamp courses at Thinkful, we've found that students learn best with:

We offer an accelerated, full-time program or a flexible part-time program data science course to allow you to choose the best format for your life. Our state-of-the-art curriculum will teach you all the skills you need to launch a successful data scientist career. Some of the highlights from our data science curriculum include:

We’ve built our programs to fit your needs and set you up for success. All courses are delivered 100% online and include advanced project-based curriculums and current industry tools to build real-world capstone projects. You can get to know our courses and formats better by exploring Thinkful 101.

Thinkful is invested in you. We want you to put your future career first today and pay tuition when you're hired. We offer a variety of payment options because your financial status shouldn’t hold you back from a new career. Explore how we work.

How can I succeed in online learning?

Since 2012, Thinkful has been helping students change their careers and lives. We help put students on an upward trajectory to last a lifetime through online learning. The Thinkful community includes nearly 600 educators and mentors and over 1,100 students who all interact 100% online. Over the last 8 years, we’ve discovered helpful techniques that ensure you learn effectively in a fully remote environment--here are some tips to setting the foundation for remote learning success.

Are there any Data Science newbie resources I can review?

If you haven’t fully realized it yet, Data Science is heavy in mathematics. Thankfully you don’t need to be a math wizard, and you can hone in on the must-have math skills needed as a data scientist.

George Mount, our data science instructional designer, outlined three key math skills that will help you succeed in the course:

He went on to explain that “[Thinkful] emphasizes practice over theory. So, while students will learn some of the hard math behind the algorithms, the emphasis is on understanding how to use them effectively in a business context.” To learn more about the specific mathematical exposure required for the program, check out the Math You Need to Know.

If you are looking to start a data scientist career, gathering expert advice is just as important as learning the technical skills of the trade. Python programming expert Giles McMullen-Klien sat down with us to share how to launch a career in data science no matter where you are in your data science career path.

His four essential tips for starting a career as a Data Scientist include:

  1. Stay connected to the Data Science community
  2. Keep an eye out for growth opportunities
  3. Find your champions and develop a relationship
  4. Highlight your achievements and teach others where you can

Dive further into Giles’ advice to get the inside scoop.

How do I get started?

If you are ready to learn more, earn more, and make a change that lasts a lifetime--schedule a call with our admissions reps to have an introductory call at a time that works for you to get started.

We will help you choose the right format and guide you through next steps to changing your career and becoming a highly paid data scientist. Our reps can also offer in-depth information on payment and financing options for the course that fits you best.

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