Become A Senior Data Scientist

October 25, 2018

 

Work on those communication and presentation skills!

 

My father was a lawyer and also an introvert, growing up he never raised his voice to us, he is just a quiet, softly spoken and lovely guy. I have seen him in court project his voice, present his case with authority and he almost seemed like another person. I asked him about how he did it, how he was so confident presenting to so many people:

 

“It’s all practice, and it is just a job, it’s what I do. I think of it no differently to a carpenter hammering a nail. What you are seeing is the result of thousands and thousands of appearances, it wasn’t always this easy.”

 

This skill can be learned with practice. Also check out this great MOOC series on public speaking.

 

 

 

Look for opportunities to mentor others

 

Mentoring others is the first step to management, is a tremendous help to those around you, but more than this teaching is the best way possible to learn. At my daughters Taekwondo class the senior ranks spend time every lesson teaching the junior ranks so that they correct and perfect their own technique in the process.

 

 

 

Understand project management methodologies

 

The Agile methodology works with changing requirements, iterative development, rapid development, regular delivery of items of work. It's a good fit for data science projects.

Check out "A manifesto for Agile data science"

 

You should also check out the Microsoft Team Data Science Process, it is absolutely comprehensive.

 

 

 

Expand your tech skills, become agnostic to the tool you use

 

As a senior data scientist you should learn both R and Python and decide which tool to use in different scenarios, you shouldn’t be bound by technologies. What you can do in R, you can also do in Python.

 

 

 

 

Full stack data science

 

Full stack data science to me is someone who is a data scientist first, who can implement solutions, but isn’t going to be the equal of a frontend developer with 20 years of experience for example.

 

So the idea is to involve yourself in the tech stack of the business, to be across it, and to know how it all fits together.

 

 

 

Continually show value to the business

 

Communication, or actually over-communication is the key here. Regular feedback and progress updates will be greatly appreciated.

 

What we do as data scientists is hard, it’s something that is hard for others to understand so we have to give feedback.

 

I have written here about having the data science team aligned to the corporate strategy, and also the need for technical leaders to manage data science teams.

 

 

If limited opportunities where you are, you can always bounce

 

 

 

You can get my latest book, The Data Scientist's Journey here: https://www.datafriends.rocks/shop

 

 

 

 

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