The Data Science Conference® provides a space where analytics professionals can network without being prospected by other attendees. This conference is by professionals for professionals.
We have created a conference where the material presented and discussed is substantial and relevant to the data science practitioner; participants don't use the conference to do business, but interact as scientists; attendees are treated with decency, dignity, and respect. This is a conference, not an Expo.
No presentation time will be allotted to sales pitches. No sponsor booths will be outside. We will not recruit you or sell your information. There will be no paid advertising. Agenda/speakers is open to the public, no email needed. Presentation slides will be provided at no extra cost (those our presenters agree to share).
We will not overcharge you. Conferences who accept sponsorship have most, if not all, of their expenses covered before selling the first ticket. But once there, the attendee sits through sponsored sales pitches. In effect, the cost is passed down to the attendee, since the attendee pays top dollar to attend already paid-for sales time.
Data scientists know that vendors and recruiters are a necessary part of our craft. That this is a vendor- and recruiter-free conference does not mean that the organizers do not recognize the importance of vendors and recruiters. The fact, however, that there is not one predictive analytics, data mining, machine learning, or data science vendor- and recruiter-free conference made us feel that there is a gap that we hope this conference fills.
We want to welcome you to The Data Science Conference®! This is your space. Get involved. Get in touch. Let us know what you think. We will listen!
Michael Tsiappoutas, the Conference Chair, has been in the financial sector (Fortune 150) for the last 13 years working on predictive modeling, machine learning, data mining, and statistical learning. He developed and taught Mathematics for Data Scientists for Lewis University's Masters in Data Science program, where he still serves on its Advisory Board. He did freelance statistical consulting, taught data analytics graduate courses and undergraduate math courses, and worked on statistical digital signal processing of early-20th-century voice signals. He holds a Ph.D. (Engineering & Applied Physics), two Masters degrees (Applied Physics; Quantitative Psychology), and a double major Bachelors degree (Psychology; Physics). He is the CEO of NeoNorm, LLC that puts together The Data Science Conference®. He lives in Connecticut with his wife and ten-year-old son, his pride and joy!