Data Scientist

I had to google what a Data Scientist does IBM has a good definition (http://www-01.ibm.com/software/data/infosphere/data-scientist/) and then I looked at a Junior Data Scientist jobs (http://www.datalabusa.com/all-careers/93-junior-data-scientist-statistician-predictive-modeler-2)

Job Skills: • Analysis of entire business problems and management solution delivery.

• Management and development of the full life cycle of model builds.

• Programming and data manipulation with SQL.

• Working with extremely large datasets/data warehouses.

• Strong data mining proficiency.

• SAS/CART/TREENET experience is a plus.

Looks like you'll need good database skills ,business and development knowledge

Database

http://teamtreehouse.com/library/database-foundations

Learning the basics of programming would be very useful

http://teamtreehouse.com/library/introduction-to-programming

Building an Application from start to finish

http://teamtreehouse.com/library/build-a-simple-ruby-on-rails-application

and business stuff

http://teamtreehouse.com/library/topic:business

Take a look at this post and its venn diagram. It is very important to understand that as a data scientist, you need a broad range of expertise beyond coding.

http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

John W. so where should I start on treehouse?

Hi Andrew Chen, we don't yet have a data science Track, but it's something we've been thinking a lot about, lately.

Sebastian Wilson, is right! There's a bunch of resources already on Treehouse that are crucial for the budding data scientist.

Here's my list:

1. Console Foundations: http://teamtreehouse.com/library/console-foundations-2

This is because many powerful tools live on the Unix command line. You'll want to use a POSIX-compliant computer (explained in course).

1. Databases and SQL: http://teamtreehouse.com/library/database-foundations

You'll need to interface with many formats of data as a DS. SQL is the most popular way for a DS to interact with a database today. Writing good and efficient queries is crucial.

1. You need version control to keep track of your work: http://teamtreehouse.com/library/git-basics

Then as recommended above, learn a bit about application development:

1. Ruby on Rails: http://teamtreehouse.com/library/build-a-simple-ruby-on-rails-application Learning Framework would also help: http://teamtreehouse.com/library/framework-basics This assumes you know HTML and CSS Basics.

This is helpful when it comes to communicating results. Dashboards and other data visualization possibilities are opened up with a web app. Also you get the benefit of learning Ruby, a general purpose language that can be used to work with data.

1. Then I'd learn visualization techniques. Learn JavaScript and D3. Start by learning Chrome DevTools Basics here: http://teamtreehouse.com/library/technology-foundations

2. Then on to JavaScript. Another language that can be used for data analysis! Although, it's primarily used with the D3 library to communicate results. http://teamtreehouse.com/library/topic:javascript

I'll finish up by saying that the hardest to get part of being a professional data scientist is the statistics background. You'll need to learn modern graduate-level statistics to be effective.

Hope this helps!

Andrew Chen -

You might be interested in checking out coursera's Data Science certificate

https://www.coursera.org/specialization/jhudatascience/1