The next frontier in data science, big data and STEM will include a healthy representation of women. What makes that statement a realistic prediction? A few key factors. The future is all about information. It will belong to those who can find it, understand it and know how to use it. Companies are looking for new ways to harness more and more information. There is a growing demand for highly skilled computer science, IT and data experts to make sense of it all to stay competitive in the marketplace.
Women are now increasingly being looked to as a homegrown, available resource to fill this bill. There are clear benefits to adding female members to the tech team including increased productivity, optimized performance and a valuable 360° perspective.
But for gender diversity to reach full scale value, a few tweaks are needed along the critical path.
In this panel discussion, we explore evidence-based benefits of welcoming more women into the tech community and of increasing female talent power on work teams.
Panelists discuss their work and achievements, the attitudes that enabled their career successes, and reinforce the value of gender diversity for inventiveness, ingenuity and business success. Displaying a contagious enthusiasm for the data science field, they describe the evolving role of the data scientist and suggest remedies to broaden the path for more women achievers to contribute their talents in what is a broad array of final products and deliverables. Panelists offer up improvements in the K-12 feeder pipeline into higher education and suggest strategies for women to thrive in STEM related fields.
The good news is that women in data, tech and STEM are getting more attention, publicity and support from all corners in what has become a global movement to readjust lopsided employment stacks in the hunt for innovation and growth.
Cornelia Lévy-Bencheton is a communications strategy consultant and writer whose data-driven marketing and decision support work helps companies optimize their performance.
As Principal of CLB Strategic Consulting, LLC., her focus is on the impact of disruptive technologies and their associated cultural challenges that open up new opportunities and necessitate refreshed strategies. She concentrates on big data, IT, Women in STEM, social media and collaborative networking.
Ms. Lévy-Bencheton has held senior marketing and strategy positions in well-known financial services firms, is currently on the Board of The Data Warehouse Institute, Tri-State Chapter, (TDWI) and the Board of the Financial Women’s Association (FWA). She earned her MA from Stanford University, MBA from Pace University and holds several advanced certificates from New York University.
Michele Chambers is an entrepreneurial executive with 25 years of technology experience, and is the President and COO at RapidMiner, which offers a predictive analytics platform. At RapidMiner, she is responsible for marketing, products and global strategy. Prior to this position, Chambers held executive leadership roles at database and analytic companies Netezza/IBM, Revolution Analytics and MemSQL. She has been responsible for strategy, sales, marketing, product management, channels and business development. Chambers holds a BS in Computer Engineering from Nova Southeastern University, and an MBA from Duke University.
Michele is the co-author of “Big Data Big Analytics” (Wiley), a book that helps businesses and IT managers/executives understand the value of big data through practical, applied analytic stories along with consumable descriptions of the enabling technology.
Alice Zheng is the director of data science at Dato (formerly GraphLab), a Seattle-based startup that offers powerful, large-scale machine-learning and graph-analytics tools. Alice loves playing with data and enabling others to do the same. She is a tool builder and an expert in machine-learning algorithms. Her research spans software diagnosis, computer network security, and social-network analysis. Prior to joining GraphLab, Alice was a researcher at Microsoft Research, Redmond. She holds PhD and BA degrees in computer science and a BA in mathematics, all from UC Berkeley.
Neha Narkhede is the cofounder and head of engineering at Confluent, a company backing the popular Apache Kafka messaging system. Prior to founding Confluent, Neha led streams infrastructure at LinkedIn, where she was responsible for LinkedIn’s petabyte-scale streaming infrastructure built on top of Apache Kafka and Apache Samza. Neha specializes in building and scaling large distributed systems and is one of the initial authors of Apache Kafka. A distributed systems engineer by training, Neha works with data scientists, analysts, and business professionals to move the needle on results.
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