Data Scientist

Data Scientist to analyses/research the data efficiently and produce more output.1.00_0_ds

“Substantive Expertise” skill – what/which questions to ask and investigate, how to interpret the data under the right context & understands the structure of the data.

For example, solving an on-line advertising problem, understand what types of people are coming to website, how they are interacting with the website. Ask the right questions like, does our ads at a certain point in the flow, or more ads at a certain time of the day? How the data is stored and structured, so it will help you work more efficiently/effectively.

It’s normal for data scientists to be stronger in some areas and weaker in others.

Real world problems with data science?
Simpson’s Paradox
A/B Testing at Obama’s 2012 Campaign
A/B testing
How to A/B testing Like a Badass
Netflix uses collaborative filtering algorithms to recommend movies to users based on things they’ve previously watched.
Bioinformatics where scientists are working on projects like annotating genomes and analyzing data sequences.
Urban Planning – solve Chicago’s bus crowding issues using data.
Public health – Analyzing electronic medical records allowed the city of Camden, New Jersey to save enormous amounts of money by targeting their efforts towards specific buildings accounting for a majority of emergency admission.
Sports – NBA teams like the Toronto Raptors are installing a new technology, sports view cameras, on the basketball courts. They collect huge amounts of data on players movement and playing styles. This helps teams to better analyze game trends and improve coaching decisions.

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