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!
HOW IT ALL STARTED!
In an early 2015 spring day, I (Michael Tsiappoutas) was attending an analytics conference with a price tag roughly double than what The Data Science Conference® charges. It felt like your normal conference—sponsor booths outside, rows of chairs, name tags, brochures, and the like. The first two or three presentations where vendor promotions of products or services. I marked each presentation with a ‘P’ for practitioner and ‘V’ for vendor. At the end of that two-day conference, 65% of the presentations were V’s! I was thinking to himself, “If any of these vendors called me up at work, I would probably direct them to the appropriate vendor evaluation and procurement channels. Why am I using company money to sit through something that doesn't develop me at all?”.
Dizzy from all the sales pitches, I went outside to get for a coffee, but no coffee was offered outside breakfast time. You'd think for that price you should be able to get coffee anytime. On my way to a café outside the hotel, I was chased by a vendor (or maybe a recruiter) for my contact info.
Later that evening, at the network drinks, what started out as a very normal conversation quickly turned into ‘let me tell you a little bit about what we offer!’ Out of the corner of my eye I spotted one of the few 'real' speakers, who talked about fraud detection. At the time, apart from my corporate job as a senior statistician with the largest auto insurer in the US, I was also an adjunct for a Data Science Masters program in Chicago. The program’s chair had asked a couple of days earlier, if I knew a good fraud detection practitioner who could design and teach a course. I introduced himself and we started talking. A lady comes and stands very close to us, practically between us. Smiling awkwardly, we asked if we could help her. She said ‘no, I’m just waiting for you to finish, so I can tell you about our services!’ She was a good, determined seller too. The awkwardness and my bowing out of the conversation didn't deter her at all! Needless to say, networking didn’t happen that day.
I went back to my hotel room troubled that night. You see, I was used to physics conferences, where people would go and talk straight science, not sell stuff to each other. I felt the data science community deserved the same, so I created The Data Science Conference®.
Five years later, the conference grew to a point that I couldn’t keep up with both my day job and the conference. I'm currently concentrating on the conference.
Thank you to all our dedicated attendees, many of whom are following us from place to place and from year to year!
Dr. Michael Tsiappoutas, the Founder and Chair of The Data Science Conference®, has been in the insurance industry (P&C Auto as well as Healthcare for Fortune 100) since 2007, working on actuarial data science, predictive modeling, machine learning, and statistical learning. An applied physicist by training, he did statistical consulting, taught mathematics and physics at community colleges and universities, taught data analytics graduate courses and undergraduate math courses, and did research on statistical digital signal processing of early 20th century voice acoustics. He had a chance to use his engineering knowledge on projects ranging from text analytics for predicting corporate litigation, to image processing for identifying fraudulent mechanics shops. He taught at Lewis University's Master's in Data Science program (where he developed and taught Mathematics for Data Scientists and served on its advisory board) and at Southern New Hampshire University's Master's in Data Analytics program. 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 (since 2008) that puts together The Data Science Conference® (since 2015). He lives in Connecticut with his wife and son.