Overview: How to become a data scientist

Do not be discouraged by the long list of things you MUST know to be a data scientist or data analyst in tech. Google Search is your friend. All of these skills (hard and soft skills) are learnable on your own if you make time to practice. I've also listed some paid online tutorials and bootcamps on the Resources page.

First  I will assume you've done some deep self-assessments of your accomplishments, transferable skills and strengths and weaknesses. As cheesy as it seems, personality tests like the Myers Briggs or Strengths Finder can give you direction when making a career transition. Make sure data science is a career that fits your strengths and work style. 

Timelines  If you already have a background in either coding or statistics (mine was in statistics), then finding a job in data science is a standard 3 - 6 month process. If you are making a total career change and starting from scratch to learn both statistics and coding, you might have a full year of practicing skills and networking before attempting interviews. 

Needed Skills  Before any interview, make sure you're confident with

  • SQL, R and Python

  • Statistics - all the basics, plus some advanced topics to discuss at a high level

  • Machine Learning - lots of buzzwords but you need to know them

  • Probabilities - at least up to a point where you come across conditional probability and Bayes' Theorem

  • Good communication skills

Advanced Topics and Nice to Haves

  • Terminal, git and GitHub, databases, database schemas, Hadoop, other Big Data management techniques ... this list goes on

  • Analytical thinking about business problems -

Most interviews are something like

  1. A phone call with a recruiter and/or whomever is doing the hiring

  2. A take home data test

  3. An onsite interview that usually lasts 3 - 5 hours, depending on the company, where they will have several 30 minute interviews with different people covering different topics. You'll be asked softball "culture fit" questions, as well as some technical code writing questions either on a computer or whiteboard (SQL, Python, R) and answer stats/probabilities questions

Check out the rest of this blog for resources on tutorials, books, blogs, and general networking information. This should be plenty to get you started!