The following sessions will take place concurrently:

Preparing for a Job Interview in Data Science: 

People with training in data science are in high demand. In this session, participants will discuss strategies for interviewing for a position in data science (including writing an effective resume and preparing a presentation) and the expectations for these positions. This session is targeted to students planning for their first job in data science as well as current professionals wanting to make the transition between academia and industry.  The session will include a formal presentation by Rita Fuller, Corporate Vice President-Advanced Analytics, New York Life Insurance Company

Decision Making in Risk Analysis: 

This breakout session will deal with more discussions of the role that could be played by adversarial risk analysis, the topic of David Banks talk, in the context of counterterrorism, setting of government regulations (for example, those dealing with pollution, drugs, opiods, etc.) where there are several interested constituents (players). Through the discussions some research problems maybe or could be identified which could then be the basis of collaborative research among conference participants.

Using Complex Inputs to Characterize Risk: 

Many adverse outcomes arise from, or can be caused by, different exposures. For example, it is not uncommon for the same cancer to be caused by multiple different chemicals, which makes determining causal relationships difficult. By using massive datasets, one can build relational models in attempt to determine causation, interaction, and the probability of the adverse event from all causes of exposure.  Recent developments in anti-terrorism research have also demonstrated that social networks may also be used to estimate the risk of an adverse event.  This breakout session will look at methods/challenges to building statistical models determine the risk from such complex inputs.