Co-Founder of Initiative for
Analytics and Data Science Standards
Hamit Hamutcu has 25 years of industry and consulting experience in the areas of analytics and data-driven business strategy. He is the co-founder at Initiative for Analytics and Data Science Standards (IADSS), launched to develop industry standards for the knowledge and skills required in data science and support building a measurement and assessment methodology for analytics and data science professionals. He is also the co-founder at Analytics Center, a company focused on capability building in data science, and an advisor or investor in several data-related initiatives and start-ups.
Previously, Hamit was a founding partner for EMEA offices for Peppers & Rogers Group and led the development of the firm in the region by serving clients across Europe, Middle East, and Africa; he was also a partner for the firm’s US office, heading up its Global Analytics Group, where he oversaw the growth of the analytics practice and helped his clients develop analytics organizations, build data infrastructure, and deploy models to support business goals. He held several positions within FedEx in Memphis in marketing analytics and technology, where he led IT and business teams to leverage the enormous amount of data the company generated to serve its customers better. Hamit is also a frequent speaker, writer, and board member at various startups and nonprofit organizations. He earned his BSc degree in electronics engineering at Bogazici University in Istanbul and his MBA degree at the University of Florida.
WATCH LIVE: November 3rd at 11:00 am
As the demand for data science talent has exploded so have the efforts to train data scientists. Programs vary widely in format, what they target, and what they emphasize in training, ranging from free online courses to full-time undergraduate and graduate degree programs. As there is not yet an agreed-upon definition of who data scientists are and which skills and knowledge they need to have, designing training programs and developing curricula remains challenging. In this presentation we will share our knowledge framework that defines the data science profession and research findings on how the training and education organizations approach this challenge.