NextGen: Data Science Day

Saturday, November 16, 2019, Bentley University.


Tentative Schedule of Events

Time

Location

Event

8:30--9:15AMRegistration
9:15--9:30AMWelcoming Remarks
9:30--10:30AMKeynote 1
10:30--10:40AMBreak
10:40--12:10PMParallel panel sessions
12:10--1:20PMLunch
1:20--2:50PMParallel panel sessions
2:50--3:00PMBreak
3:00--4:00PMKeynote #2
4:00--6:00PMPoster / networking reception

Sponsor Interviews

We are pleased to announce that there will also be an opportunity for sponsors to set up interview sessions throughout the day with attendees. Interested sponsors should check out the sponsorship details. Interested attendees should opt in for sponsorship contact and upload their resume/CV during registration.

Parallel Sessions

We will have a total of 3 panel sessions plus 1 hands-on workshop running in the two parallel sessions. We will later decide which sessions to run in parallel to each other based on attendee interest, expressed upon registration.

The four sessions are:

  1. Business Analytics in Practice: This session will feature 3-5 speakers that will present on a business challenges and how they used data science or statistical techniques to address the challenge. The focus will be on how statistics and data science can be used to address questions that arise in business settings. Q&A session to follow.
  2. Challenges in Data Science: This session will feature 3-5 speakers addressing open questions in data science and statistics. For example, data ethics, reproducibility, visualization, leading with data science / statistics, communication, education, etc. Q&A session to follow.
  3. Careers in Data Science: This session will feature 3-5 speakers that will present broadly on tips for finding jobs, interviewing well, data science applications, preparing for the job market, how they came to their position, job search timelines, etc. Q&A session to follow.
  4. Workshop: This session will feature a speaker spending the time on an interactive workshop. Topic to be decided from: programming a specific language (e.g., specific packages within R or Python, Spark), visualization (e.g., Tableau), reproducibility, or on more technical topics, such as working with missing data, model selection, etc.

Conduct Policy

Data Science Day promotes the free expression and exchange of ideas. All participants agree to abide by the American Statistical Association's conduct policy listed here.