RSS Featured Blog Posts
  • 3 Reasons to Learn the Expected Value Framework for Data Analysis
    One of the most difficult and most critical parts of implementing data science in business is quantifying the return-on-investment or ROI.  In this article, we highlight three reasons you need to learn the Expected Value Framework, a framework that connects the machine learning classification model to ROI.  …
    Matt Dancho
  • Remotely Send R and Python Execution to SQL Server from Jupyter Notebooks
    Introduction Did you know that you can execute R and Python code remotely in SQL Server from Jupyter Notebooks or any IDE? Machine Learning Services in SQL Server eliminates the need to move data around. Instead of transferring large and sensitive data over the network or losing accuracy on ML training with sample csv files, […]
    Kyle Weller
  • Weekly Digest, July 16
    Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. Featured Resources and Technical Contributions Best Machine Learning Tools:…
    Vincent Granville
  • Critically Reading Scientific Papers
    Critically reading scientific papers is critical for Data Scientists working some areas - especially those working in health. With that in mind, here are some key considerations in reading scientific (peer-review, grey literature) papers: Theory: Is the theory sound? Are there theoretical issues in the design that cause…
    Howard Friedman
  • The art of data science...
    In 2018, Fast Company declared ‘Data Scientist’ as the best job in America for the third…
    Ziyad Nazem

Located in DFW? Or, love to visit here. Learn at Divergence Academy, hands-on with instructor, certificate granting career college approved by the Texas Workforce Commission.

 

A Career Strategy for Data Science

Candid Advice from Paco Nathan, Data Scientist and O’Reilly Author

How to become a data scientist, by Vish Puttagunta, Sr. Data Scientist at AT&T

 

Biography

Paco Nathan is Director, O’Reilly Learning. Known as a “player/coach” data scientist, he has led innovative Data teams building large-scale apps for several years. As a recognized expert in distributed systems, machine learning, and Enterprise data workflows, Paco is an advisor for Amplify Partners and Galvanize. He has 30+ years technology industry experience ranging from Bell Labs to early-stage start-ups. Newsletter and “official” web site: http://liber118.com/pxn/

Data Science Salaries

Excerpt from “O’Reilly Media has been conducting an annual survey for data professionals, asking questions primarily about tools, tasks, and salary — and we are now releasing the third installment of the associated report, the 2015 Data Science Salary Survey. The 2015 edition features a completely new graphic design of the report and our findings. In addition to estimating salary differences based on demographics and tool usage, we have given a more detailed look at tasks — how data professionals spend their workdays — and titles.”

And, here’s the 2016 Data Science Salary Survey.

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