How does a healthcare data dive happen?

Well, you get a couple of beers with your friends at an East Village bar, you start talking about healthcare, you start talking about data, you get really enthusiastic, you start emailing your friends. They like the idea, they get on board, you start meeting regularly and you realize ... it’s a lot of work to plan a data dive!

Then, you continue meeting regularly ...

Planning the data dive has been and still is a lot of work, yes, but also a lot of fun. We, the organizers, all knew each other somehow (six degrees of separation). The experience of organizing the data dive provided us with the opportunity to see each other regularly (great!) and to do what we like: address an important problem and work towards a common goal with data.

There are going to be no prizes at the data dive, instead we focus on collaborative effort. The goal is important, let’s work together. Besides fixing healthcare, we hope to provide people with the opportunity to learn from each other. You are great at R, learn from someone who knows python. You are into SQL, perhaps you’d like to try visualization?

If you are into the same stuff, we hope to meet you at the data dive. Looking forward to it.


Anasuya Das
Data Scientist

Anasuya is currently a data scientist at Memorial Sloan Kettering Cancer Center. She is excited to use data science to improve cancer care. In her past life she helped stroke patients improve their vision. Today she can be found cleaning messy hospital data, using predictive modeling to improve health care and optimizing the perfect blend of coffee beans.


Courtney Epstein
Data Scientist

Courtney works to bring power to the patient as a data scientist at ZocDoc. She’s excited by how technology helps people make informed choices about their care. She is looking forward uncovering global trends in healthcare as part of this event.


Friederike Schüür
Program Director

I once sat in a doctor’s chair and realized I was unable to afford the medical treatment I needed. And it’s not even that I didn’t have insurance. It was a bad day. I believe tech and data has the potential to change healthcare for the better: increased transparency for a start will help you make informed decisions about your health. As a Program Director at Insight Data Science, and former Data Scientist at Oscar, I’m lucky enough to be part of the data science community in New York and excited about what we can achieve if we set our minds to it.


Iva Vukićević
Data Scientist

As a Data Scientist at Macy’s I know how much power good data analysis has in improving efficiency in the corporate setting. To me, the vast sources of open data present an opportunity for the average citizen to contribute in changing policy and I am excited to be a part of an event that can potentially reduce cost in the healthcare sphere.


Laurence De Torrenté
Research Fellow

With a background in statistics, I am now working as a postdoc in bioinformatics at the Albert Einstein College of Medicine. After helping biologists and physicians make sense of their data, I am excited to uncover the secrets of healthcare with all of you!


Sean Quigley
Data Engineer

Sean works as a data engineer at Shutterstock building large-scale, high-performance data systems. He enjoys working on challenging data problems; particularly engineering elegant solutions to empower data science. Despite his limited experience in the health-care space, he was excited to work on a new problem with some very smart and cool people.


Shani Offen
Data Scientist

Shani got her PhD in computational neuroscience from NYU in 2008. Her research focused on cognition and brain imaging, utilizing methodologies including clustering, dimensionality analysis, and multiscale filtering. She is currently a senior data scientist at the online publisher, where her team looks at signals from billions of sessions by hundreds of millions of visitors to millions of articles on thousands of topics from hundreds of countries over tens of years. Needless to say, it's really fun.


Sinziana Eckner
VP Core Modeling

Sinziana is a quantitative modeler at JPMorgan Chase. As an advocate for women in technology, Sinziana is an organizer of the “NYC Women in Machine Learning and Data Science” meetup. She is also a passionate supporter of the open data movement and is excited about shaping the policy debate together.