Tech Careers and Data Science: Presentations
Data scientists navel gazing in a corner? Engineers not thinking, just refactoring? Product managers just making slides? That’s no way to build data products! Is it possible for them to play well together? I will share my experiences about what works (and what doesn’t), in building highly productive cross-functional teams that build innovative data products. I will provide practical tips for how to structure teams in companies of all sizes.
As evidenced at GHC, women are important contributors in computer science. However, they remain significantly underrepresented in the tech workforce. African Americans, Hispanic Americans, and Native Americans face similar underrepresentation issues. In this work, we describe how data science can play a key role in driving change. We consider the use of data fusion, mining, analysis, and visualization to elucidate the tech environment while protecting the privacy of individuals
Data science is so rich a field that companies tend to hire for specific areas of focus. Data scientists usually concentrate on statistical analysis, and data engineers develop supporting software. But when you’re at a startup, you work on the full stack of data and you do so scrappily. I explain how to build systems to aggregate and serve data and discuss analytical problems I’ve tackled from the startup point-of-view.