Building an End to End Data Science team - Focusing on the Solution.
In most organizations, Data Science has broken through the “Why” and the “What” questions, but is stuck on the “Who” and the “How“. Who do I need on a Data Science team and How do I integrate their skills with the existing organization to be successful? From my experience, I have only seen one solution that provides sustainable success in developing Data Science as a new capability. A rock star Data Scientist may be able to bring a couple projects to the finish line but can’t scale, a cross functional team lead by a coordinating body struggles with innovation and fast delivery. I’ll provide my perspective on a hybrid solution based Data Science team which scales with distributed and semi-specialized work, supports agile analytical development and sustainably innovates when delivering solutions.
Matt Shump has over 10 years of experience executing and leading the development of analytical capabilities that focus on driving actionable insights specializing in: Data Science, Big Data Analytics and Predictive Analytics. He has worked in a wide range of industries solving analytical challenges, most recently at Cigna leading cross functional analytics, Big Data and app development teams to productize the data to insight delivery process. Prior to that, he developed the Advanced Analytics and Data Science capabilities at Endurance International Group in route to an IPO. Matt’s holds an MS in Mathematics & Statistics as well as a Black Belt in Lean Six Sigma.
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