Schedule: Culture and organization sessions

Hiring teams largely rely on both intuition and experience to scout talent for data science and data engineering roles. Drawing on results from analyzing over 15 million jobs and their outcomes, Maryam Jahanshahi interrogates these “common sense” judgments to determine whether they help or hurt hiring of data scientists and engineers. Read more.

A/B testing has revealed the fallibility in human intuition that typically drives business decisions. Eric Colson and Daragh Sibley describe some types of systematic errors domain experts commit, explain how cognitive biases arise from heuristic reasoning processes, and share several mechanisms to mitigate these human limitations and improve decision making. Read more.

Many organizations look to add data science to their skill portfolios through the hiring of data science experts. Dave Stuart shares a complementary way to build a data science-savvy workforce that nets tremendous value by using Jupyter to add introductory data science practices to domain experts and business analysts. Read more.

Data Science University (DSU) was established to bring analytics education to UnitedHealth Group, the world’s largest healthcare company, with over 270,000 employees. Marc Paradis explains how DSU was built out over time in an era of rapidly changing analytics technology and capabilities in an industry ripe for disruption, covering the challenges faced and lessons learned. Read more.

Francesco Mucio tells the story of how Zalando went from an old-school BI company to an AI-driven company built on a solid data platform. Along the way, he shares what Zalando learned in the process and the challenges that still lie ahead. Read more.

What happens when you have a data science organization but no data engineering organization? Jesse Anderson and Thomas Goolsby explain what happened at USAA without data engineering, how they fixed it, and the results since. Read more.