Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and
International Administration, co-author of Monetizing Machine Learning and VP of Data Science at SpringML.
From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say:
It just ain’t real 'til it reaches your customer’s plate
I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied machine learning.
Whenever I am asked how to break into this field, I reply, ‘push it out into the public domain on a regular basis’.
Being a blogger and liking the sound of my voice, I unfortunately murk it up with more stuff, like taking classes on Udacity and Coursera, participating in competitions on Kaggle, and getting a degree in data science. But, at the top of the list, will always be, create, invent and push out regularly!
It may go against the grain within some organizations, so don’t share trade secrets or other people’s IP; but there’s always something within your skillset that others will find interesting.
It’s a miracle technique! It’s isn’t about quantity or quality but about doing it on a regular basis and building that production muscle—it becomes magic! It will take you to unexpected places.Kind of like compounding interest or butter in your coffee—there’s no downside to this approach!