Episode 40: Making Data Science Teams Profitable

For many people, data science is synonymous with machine learning and many data science courses are little more than overviews of the most used machine learning algorithms and techniques.

Where the majority of data science courses fall short is they neglect to bridge the gap between data science theory and business reality, resulting in many data scientists who are technically strong but unable to create value from their work. However, this doesn’t necessarily have to be the case.

In this episode, Douglas Squirrel joins Dr Genevieve Hayes to discuss systems and techniques data scientists and their managers can use to make data science teams profitable.

Guest Bio

Douglas Squirrel has been coding for forty-five years and has led software teams for twenty-five. He uses the power of conversations to create insane profits in technology organisations of all sizes. His experience includes growing software teams as a CTO in startups; consulting on product improvement; and coaching a wide variety of leaders in improving their conversations, aligning to business goals, and creating productive conflict.

Highlights

• Douglas Squirrel’s journey: From CTO to profitability guru (00:00)
• Integrating data science with business goals (10:58)
• The surprising technological growth in Africa (17:38)
• Overcoming the Walled Garden: strategies for tech team success (19:14)
• The Lean Startup approach to data science (26:48)
• The importance of direct feedback in data science (32:50)
• Transforming data science with human empathy (33:39)
• Leveraging action science for effective communication (42:46)
• Elephant Carpaccio (47:41)
• Techniques for data scientists to create business value (51:22)
• Creating productive conflict for business innovation (53:43)
• Final thoughts and resources (01:00:28)

Links

• Douglas Squirrel’s website
• Squirrel Squadron
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE