How to Become a Data Scientist

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The Data Scientist role is expanding. Google Trends data shows that number of times people searched for “data scientist” steadily increased each month throughout 2018. Unsurprisingly, the top five related queries are all related to a career as a data scientist.

Some other related topics from this data show that people are looking for more information on education. “Software engineering”, “probability theory” and “deep learning” take the top three spots. The related topics and related queries both confirm the popularity of this career and the increasing desire to break into it.

Beyond this data, what are the skills needed to steer your career towards this role? What geographic locations should you focus on? Which industries are the most popular?

Here’s the breakdown.

Skills needed to be successful

  1. Knowledge of algorithms, statistics and mathematics
  2. Broad and deep knowledge of programming languages, such as R, Python and SQL
  3. Experience structuring a data solution, from identifying the right questions to ask, to performing the analysis, to communicating results to the team
  4. Hadoop experience
  5. Machine learning and AI
  6. Data visualization
  7. Preparing and analyzing unstructured data


Locations

Where should you look for a career in data science? The top 10 cities searching for “data scientist” in 2018 were:

  1. Sunnyvale, CA
  2. Jersey City, NJ
  3. San Francisco, CA
  4. Seattle, WA
  5. Boston, MA
  6. San Jose, CA
  7. Austin, TX
  8. Washington, D.C.
  9. New York, NY
  10. Chicago, IL


Salaries

According to Glassdoor, Data Scientists make an average salary of $139,840. If you’re motivated by pay, Tech, Software, Media & Publishing and Retail industries pay the most, while Government, Consumer Services, Consumer Electronics and Accounting & Legal industries pay the least. As company size grows, the potential earnings of a Data Scientist also increases. And as expected, as you gain more experience as a data scientist, you also earn more. The largest jumps are made from 3-6 years of experience and after surpassing 15 years of experience.

As you look to springboard your career to become a Data Scientist, it’s important to remember that there are many paths. The same entry-level position that led to this role for one person may not work for another. Focus on honing the skills we gathered, and search for data science-related roles in the areas suggested above to improve your odds. A career is a marathon, not a sprint. But with dedication to your craft, the right combination of skills, and a strong work ethic, you’ll become a Data Scientist in no time.

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