What are managers looking for in a Data Analyst and a Data Science position, what skills do they require and how do they define and compare these positions within a business?
Top 5 Findings
Like the previous ebook, it opens with the top 5 take aways from the interviews, which were:
The information revolution is real.
Data analytics is becoming increasingly accessible.
Do your own projects to break into the industry.
Statistics is more important than programming.
The most important skill is being able to ask the right questions.
I think that last point is quite understated. A word repeated over and over again was curiosity. Interviewees stressed that technical skills like statistics and SQL can be taught, but curiosity and a love of data are innate.
Interviewees
The ebook is 43 pages long and again you will be able to read it very quickly. There are 9 interviewees from 8 companies, specifically:
My favorite interviews were with Dean Abbott and David Gerster, perhaps because I took the most notes. Below are some key points from my notes taken from across the interviews.
You can get a long way by counting and summing things, model building can be expensive.
An analysis that does not turn into a decision in the business is basically a waste of time.
When working or presenting work focus on the beginning (framing) and end of the problem (recommended actions).
Data Analysts answer questions with provided data, Data Analysts define the problem and collect the data and deliver answers.
Think about domains where business decision making is driven by intuition, they are ripe for disruption (sports, fashion, etc.)
Resources and books are not mentioned enough in these interviews. Dean did list off a few books he recommends, which were:
Thanks for sharing your thoughts on this book. It looks interesting and fun for a quick read.