Statistical ScienceThe 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 stat-msd@duke.edu.
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
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 ResourcesSep. 1, 2021 Catherine L. Allen, Career Specialist, Duke Career Center, Dr. Aaron Colton, Lecturer, Thompson Writing Program |
Liberty Mutual OverviewSep. 8, 2021 Eden Huang, Data Scientist, Liberty Mutual, Daniel McCarthy, Senior Campus Recruiter, Liberty Mutual
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Writing Effective Resumes WorkshopSep. 15, 2021 Dr. Heidi Scott Giusto, Career Coach, Career Path Writing Solutions |
Learn to Love LinkedInSep. 22, 2021 Lora B. Poepping, President, Plum Coaching & Consulting |
Internship Lightning TalksSep. 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 Information SessionOct. 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). |
Communicating Effectively in a Professional Setting, Let by Farnoosh Brock, Training & CoachOct. 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. |
Ph.D. Career DiscussionOct. 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. |
Ethical AI & Data ScienceNov. 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 DukeJan. 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 diseaseFeb. 3, 2021 Dr. Michael Lutz, Associate Professor, Department of Neurology, Duke University School of Medicine |
Increasing Trust and Interpretability in Machine Learning with Model DebuggingFeb. 10, 2021 Patrick Hall, Principal Scientist, bnh.ai |
Top 3 Things I've Learned in 3 Decades of Data ScienceFeb. 17, 2021 Dr. John Elder, Founder & Chair, & Kimberly Kaiter, Data Scientist, Elder Research |
Delivering Successful PresentationsFeb. 24, 2021 Dr. Melissa Bostrom, Assistant Dean for Graduate Student Professional Development, Duke Career Center |
Statistics in the Government: Transparency, Leadership, and CollaborationMar. 3, 2021 Dr. Simone Gray, Sr. Statistician, Center for Disease Control and Prevention |
Analytical Life Cycle of Model Development at Discover Financial ServicesMar. 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 sciencesMar. 24, 2021 Dr. Surya Tokdar, Associate Professor, Duke Statistical Science |
Introduction to Mathematical OptimizationApr. 7, 2021 Dr. Matt Galati, Distinguished Operations Research Specialist, SAS Institute |
Project Phoenix: Predicting AAP sales under COVIDApr. 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 |