Episode 14 — Drew Conway

“A well-articulated business problem is an essential first-step to any successful data science endeavor” – Drew Conway

Drew Conway is a world-renowned data scientist, entrepreneur, author, and speaker, perhaps most well-known for his infamous 2010 “Data Science Venn Diagram”.

Today, Drew is the Founder & CEO of Alluvium: a company using machine learning and AI to turn massive streams of data produced by industrial operations companies into insights that bridge the gap between big data and human expertise.

Designed with the goal of helping industrial operations become safer, more efficient and more profitable, the Alluvium platform makes industrial machine data meaningful and useful to the people who rely on it to make decisions that affect the stability of their operation.

Before starting Alluvium in 2015, Drew helped start:

Data Gotham: an organization focused on supporting the NYC data community, with an annual conference bringing together people from all industries
DataKind: a non-profit that brings high-impact organizations together with leading data scientists to use data science in the service of humanity. They enable data scientists and social changemakers to address tough humanitarian challenges together, ranging from education to poverty, health to human rights, and the environment to cities.

After starting the conversation by exploring Drew’s early years, we focused most of the dialogue around his (quite frankly, brilliant) thought process around identifying the highest-impact, most-needed applications for data science across problem spaces.

Some of my favorite talking points included:

Why “force of will” and a “tendency toward combativeness” were key to Drew’s early development and overcoming imposter syndrome
Lessons learned from his 4th grade teacher who told him he was bad at math and an AAU basketball coach who made his team find their way home from the outskirts of Las Vegas
The questions Drew asks executives who tell him they want to hire a data science team, how he recommends they avoid being “seduced by the industry” and “return back to first principles”
Drew’s process for determining new applications for data science within various industries
The three-question mental model Drew used to identify Alluvium’s first major product offering: business problem → data available → human support
Alluvium’s team-building and hiring philosophy, how it’s evolved from day one until today
The story behind DataKind, how he and his team decided what nonprofits to start by working with, and the step-by-step process they took to testing their assumptions