Kevin Barth Email & Phone Number

IBM reports that 90% of all online data has been created in the past two years. So, how do we distinguish important, actionable information from random noise?Determining the intentionality behind the analysis is the first step. Segment out what really matters to make finding significant variables far easier.Most importantly, spending the time to intensely clean the data will ensure its insights are reliable. A beautiful, ornate mansion built on loose soil will be worth nothing; similarly, a fancy algorithm will have no meaning if the data isn't properly postured. Putting the effort in at the beginning of a project will make conducting the analysis far easier.Finally, ensuring that your analysis is objective is critical to future success. We all have underlying biases, and in the words of Ronald Coase, "if you torture the data long enough, it will confess to anything." Having an open mind will help you see past the insights that you want the data to produce and can lead to unexpected yet rewarding outcomes.I continually work to use these guiding factors as the groundwork for any project. When working in teams, being educated in the intersection of business and data science, I use my verbal skill set to ensure all members understand each piece of the puzzle as we produce a cohesive final product. I am happy to put these skills to use every day as a Data Scientist for IBM.

Listed skills include Leadership, Financial Modeling, Public Speaking, Microsoft Office, and 4 others.