Statistical Science Proseminar

The proseminar course – STA 581 – includes informational seminars from experts from inside and outside of Duke University, including faculty, industry professionals, career center staff, and administrators from institutes and centers around Duke.

Students learn various ways to apply their degree, strategies for getting the most out of their two-year program, types of internships and career options, methods to apply for jobs/internships, communication, presentation, leadership coaching, and more.

The course format is mostly interactive; however, sometimes, the presentations may be lecture-style followed by questions. Many students have found job and internship opportunities after networking with our featured speakers.

The students registered for the proseminar course expected to attend and actively participate in all sessions. Some proseminar sessions are open to all StatSci students and faculty. If any StatSci student or faculty member wishes attend a proseminar, please email

Instructor: Funda Gunes
Day/Time: Wednesday, 3:30 pm to 4:45 pm US Eastern

Upcoming Proseminar Events

There are no upcoming events at this time.

Past Proseminar Schedules/Events

Funda Gunes
Syllabus and Career Resources (MSS tracks/events/interviews etc.)

Aug. 25, 2021

Dr. Funda Gunes, Director of Master's Program, Duke Statistical Science
Duke Career Center Resources and Thompson Writing Program Resources

Sep. 1, 2021

Catherine L. Allen, Career Specialist, Duke Career Center, Dr. Aaron Colton, Lecturer, Thompson Writing Program
Liberty Mutual
Liberty Mutual Overview

Sep. 8, 2021

Eden Huang, Data Scientist, Liberty Mutual,  Daniel McCarthy, Senior Campus Recruiter, Liberty Mutual


Dr. Heidi Scott Giusto, Career Coach, Career Path Writing Solutions


Writing Effective Resumes Workshop

Sep. 15, 2021

Dr. Heidi Scott Giusto,   Career Coach, Career Path Writing Solutions
Lora B. Poepping, President, Plum Coaching & Consulting


Learn to Love LinkedIn

Sep. 22, 2021

Lora B. Poepping, President, Plum Coaching & Consulting
Internship Lightning Talks

Sep. 29, 2021

Second-year Statistical Science Master's Students will give lightning talks about their summer internship experiences. Emre Yurtbay, Internship at Facebook Lingyu Zhou, Internship at Voya Financial Michael Sarkis, Internship at 2nd Order Solutions Madeleine Beckner, Internship at Lubrizol Jack McCarthy, Internship at Autodesk Rob Kravec, Internship at Optiver.
Home Depot
Home Depot Information Session

Oct. 6, 2021

As a Manager of a newly formed Data Science team,. Jonathan Weininger will share his experience building a Data Science team. This will include what it has been like to host 25+ interviews of data science and analytics candidates. Prior to leading a Data Science team, Jonathan helped and analytics team mature from primarily rear-view mirror reporting (descriptive) to predicting and helping shape the business (prescriptive/predictive).
Photo of Farnoosh Brock
Communicating Effectively in a Professional Setting, Let by Farnoosh Brock, Training & Coach

Oct. 16, 2021

Students will explore their workplace identities and perceived pressures, as well as learning  interpersonal tools to develop their self-confidence and find their voice. Students will learn about fixed and growth mindset and develop tools for self-reflection. We te4ach students to work collaboratively and avoid miscommunication, and leave with practical tools and strategies to implement. 
Photo of Old Chemistry
Ph.D. Career Discussion

Oct. 20, 2021

Gong Jessie, University of Texas-Austin, Bo Liu, Duke University, Morris Greenberg, University of Toronto, Gauri Kamat, Brown University,  Christine Shen, Duke University and Dr. Merlise Clyde, Director of Graduate Studies, Duke University Statistical Science. 
Photo of Emily HGadley, RTI
Ethical AI & Data Science

Nov. 17, 2021

Ethical AI & Data Science: As statisticians, data scientists, students, and teachers, we collect data, store data, transform data, visualize data, and ultimately impact how data are used. With this responsibility, it is imperative that we confront the ways in which data and algorithms have been used to perpetuate biases and eliminate discriminatory choices and algorithms in our own work. Join a conversation where we discuss the landscape of ethics in AI and data science. 
Collaborative Research at Duke

Jan. 27, 2021

Dr. Gina-Maria Pomann, Director; Duke CTSI Biostatistics, Epidemiology and Research Design (BERD) Methods Core
Building a better mouse model of Alzheimer’s disease

Feb. 3, 2021

Dr. Michael Lutz, Associate Professor, Department of Neurology, Duke University School of Medicine
Increasing Trust and Interpretability in Machine Learning with Model Debugging

Feb. 10, 2021

Patrick Hall, Principal Scientist,
Elder and Keiter
Top 3 Things I've Learned in 3 Decades of Data Science

Feb. 17, 2021

Dr. John Elder, Founder & Chair, & Kimberly Kaiter, Data Scientist, Elder Research
Delivering Successful Presentations

Feb. 24, 2021

Dr. Melissa Bostrom, Assistant Dean for Graduate Student Professional Development, Duke Career Center
Statistics in the Government: Transparency, Leadership, and Collaboration

Mar. 3, 2021

Dr. Simone Gray, Sr. Statistician, Center for Disease Control and Prevention
Dickerson and Kulkarni
Analytical Life Cycle of Model Development at Discover Financial Services

Mar. 17, 2021

Dr. Steven Dickersen, Chief Analytics Officer, & Dr. Raghu Kulkarni, VP of Data Science, Discover Financial Services
Applications of Bayesian function estimation in neuroscience and environmental sciences

Mar. 24, 2021

Dr. Surya Tokdar, Associate Professor, Duke Statistical Science
Introduction to Mathematical Optimization

Apr. 7, 2021

Dr. Matt Galati, Distinguished Operations Research Specialist, SAS Institute
Project Phoenix: Predicting AAP sales under COVID

Apr. 14, 2021

Advance Auto Parts Team: Sukanya Chaudhuri, Sr. Manager, Marketing Analytics & Data Science; Scott Smith, Data Scientist, Data Science; Joan Pharr, Associate Data Scientist, Marketing Analytics & Data Science; Justin Ward, Marketing Analyst, Marketing Analytics & Data Science; Liping Wu, Data Scientist, Marketing Analytics & Data Science; Kristen Biddle, Data Scientist, Data Science