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.
Characterization of Risk of Multidimensional Outcomes:
For hazards describable as univariate outcomes, one can characterize the risk or hazard by estimating probability distributions; however, when the hazard is multivariate (e.g. multiple tumor sites, functional responses) properly representing the underlying risk distribution is more difficult, making it challenging to account for the probability of an adverse event. This breakout session will discuss challenges to characterizing the probability distributions of these hazards.
Estimating the Risk of Rare Events from Large Datasets:
For many hazards, the adverse event under consideration has a low probability of occurrence and are thus difficult to study directly; however, there may be other events, correlated to the adverse event, which precede the event of interest, and can predict the outcome of interest. This break out session discusses methodologies using large datasets to build correlative predictive models that can predict rare events.