E. Shin Oblander

About Me:

  • I am a doctoral student in the Marketing division of Columbia Business School.

  • I am an empirical methodologist focusing on statistical and econometric methods. I develop methods to address novel business problems stemming from changes in the marketing analytics environment such as the rise of third-party data sources, privacy regulations, and unstructured data.

  • My methodological areas of interest include causal inference, selection correction/external validity, and representation learning for unstructured data. My substantive areas of interest include customer relationship management, consumer choice, and digital marketing.

  • My research has been published in Marketing Science.

  • I am in the 98th percentile of authors on SSRN in terms of paper downloads.

Curriculum Vitae:

  • See my most current CV here.

Contact Info:


  • PhD Marketing (Quantitative track), Graduate School of Business, Columbia University (August 2018 - Present)

    • MPhil Marketing conferred February 2021

    • Fellowships: Provost Diversity Fellow, Lead Teaching Fellow, Deming Center Doctoral Fellow, Amanda and Harold J Rudolph Doctoral Fellow

    • Adjunct instructor for MS in Marketing Science course "Statistical Modeling and Decision Making"

    • GPA 10.62/11.00

  • BS Economics, The Wharton School of the University of Pennsylvania (August 2013 – May 2018)

    • Honors: Summa Cum Laude, Dean's Award for Excellence, Dean's List 2013-2018

    • Concentrations: Statistics and Actuarial Science

    • Minors: Mathematics and Japanese Studies

    • GPA 3.95/4.00

  • Exchange Student, Faculty of Economics at Hitotsubashi University (March 2017 – August 2017)

    • GPA 4.30/4.30


Working Papers

Published and Forthcoming Papers

  • McCarthy, Daniel Minh; Oblander, Elliot Shin (2021). "Scalable Data Fusion with Selection Correction: An Application to Customer Base Analysis." Marketing Science, 40(3), 459-480.

  • Oblander, Elliot Shin; Gupta, Sunil; Mela, Carl F.; Winer, Russell S.; Lehmann, Donald R. (2020). "The Past, Present, and Future of Customer Management." Marketing Letters, 31(2), 125-136.

  • Oblander, Elliot; Park, Sojung Carol; Lemaire, Jean (2016). "The Cost of High Suicide Rates in Japan and the Republic of Korea: Reduced Life Expectancies." Asia-Pacific Population Journal, 31(2), 21-44.


Instruction (Columbia Business School)

  • Fall 2020, Fall 2021, Fall 2022: Statistical Modeling and Decision Making

    • Columbia Business School MS in Marketing Science course

    • Instructor rating: 4.7/5 (2020), 4.6/5 (2021), 4.4/5 (2022)

Teaching Assistantships (Columbia Business School)

  • Fall 2021, Fall 2022: Analytics in Action, Professors Daniel Guetta and Brett Martin

    • MBA course

  • Spring 2022: Customer Management, Professor Kinshuk Jerath

    • MS course

  • Fall 2021: Applied Multivariate Statistics, Professor Kamel Jedidi

    • MS/PhD course

  • Spring 2021: Pricing Strategies, Professor Asim Ansari

    • MS course

Teaching Assistantships (The Wharton School)

  • Spring 2016, Summer 2016, Spring 2017, Summer 2017, Fall 2017, and Spring 2018: Applied Probability Models in Marketing, Professor Peter Fader

    • Spring 2016, Spring 2017, and Spring 2018: Undergraduate/MBA cross-listed course

    • Summer 2016, Summer 2017, and Fall 2017: Executive MBA course

  • Fall 2015: Risk Management, Professor Gregory Nini

    • Undergraduate/MBA cross-listed course

Fellowships and Scholarships:

  • Deming Center Doctoral Fellow, 2020-2021.

  • Columbia Business School Amanda and Harold J Rudolph Fellow, 2020-2021.

  • Columbia University Center for Teaching and Learning (CTL) Lead Teaching Fellow (LTF), 2020-2021.

  • Columbia University Provost Diversity Fellow, 2018.

  • Casualty Actuaries of the Mid-Atlantic Region Scholarship Recipient, 2016.

  • Two-time Wharton Summer Program for Undergraduate Research (SPUR) Scholar, 2015 & 2016.

Student Testimonials:

Anonymous student comments from end-of-term course evaluations

  • Fall 2021 (Instructor for Statistical Modeling and Decision Making)

    • "Elliot is one of the most dedicated teachers I have ever had. He puts a lot of effort into the lectures and making sure the students understand the concepts given in the class. Furthermore, he is also very open and will always provide a helping hand, which is really appreciated in a hard course such as this one. Hands down one of the best stats teachers."

    • "I loved Elliot's passion and commitment towards the subject. He is an amazing instructor, willing to help and deepen any topic during and after class!"

    • "I love Elliot! He was helpful and always knew the answer to literally every question someone asked."

  • Fall 2020 (Instructor for Statistical Modeling and Decision Making)

    • "Elliot is a really nice person who is very engaging and insightful!"

    • "Extremely helpful instructor... Very powerful lecturing."

    • "Elliot was very clear in his teaching and obviously put in a ton of work prepping for class each day. He’s brilliant and very approachable when you need help."

  • Summer 2016 (TA for Applied Probability Models in Marketing)

    • "Elliot, the T/A, was awesome! He seems to know the material almost as well as the professor! He is very supportive, easy going, and extremely helpful. He is far and away the best T/A I've experienced in the program. He really went the extra mile for our class. You should give him some award or something. I'm confident he will do amazing things in his future!"

    • "Elliot was a fantastic TA. Very accessible and understood the concepts very well. He could be an instructor. Hold on to him!"

    • "Shout out to Elliot Oblander, our TA. He was really excellent in supporting Professor Fader and doing the 'mop up' with us after our brains were completely blown out. He was very, very accessible outside of class... and you can tell he really gets this stuff and likes helping students. He will be a great professor someday, if that's what he wants to do."

Doctoral Coursework:

Columbia University

  • Decision, Risk, and Operations

    • Reliable Statistical Learning: Professor Hongseok Namkoong, Fall 2020

  • Economics

    • Econometrics I: Professors Gregory Cox & Jose Luis Montiel Olea, Fall 2018

    • Econometrics II: Professors Jushan Bai & Simon Lee, Spring 2019

    • Industrial Organization III: Professor Andrey Simonov, Spring 2019

    • Micro-Econometrics: Professor Simon Lee, Fall 2019

    • Computational Models of Perception and Choice: Professor Michael Woodford, Spring 2020

  • Marketing

    • Analytical Models: Professor Kinshuk Jerath, Fall 2018

    • Consumer Behavior I (Information Processing): Professors Michel Pham & Bernd Schmitt, Fall 2018

    • Empirical Models: Professor Asim Ansari, Fall 2018

    • Mathematical Models: Professor Rajeev Kohli, Fall 2019

    • Bridging Behavioral Economics and Marketing Science: Professor Ran Kivetz, Fall 2019

    • Consumer Behavior II (Judgment and Decision Making): Professor Eric Johnson, Spring 2020

    • Marketing Decisions and Methods: Professor Donald Lehmann, Summer 2020

  • Statistics and Computer Science

    • Foundations of Graphical Models: Professor David Blei, Fall 2018

    • Applied Causality: Professor David Blei, Spring 2019

    • Representation Learning (A Probabilistic Perspective): Professor David Blei, Spring 2020

University of Pennsylvania

  • Computer Science

    • Machine Learning: Professor Shivani Agarwal, Spring 2018

  • Marketing

    • Empirical Models in Marketing: Professor Eric Bradlow, Spring 2017

  • Statistics and Biostatistics

    • Bayesian Methods and Computation: Professor Shane Jensen, Spring 2016

    • Big Data for Biomedical Research: Professor Hongzhe Li, Fall 2016

    • Statistical Methodology: Professor Andreas Buja, Fall 2017

  • Operations Research

    • Stochastic Processes I: Professor Maria Rieders, Fall 2015

    • Stochastic Processes II: Professor Maria Rieders, Spring 2016

    • Dynamic Programming: Professor Maria Rieders, Spring 2016

Hitotsubashi University

  • Economics

    • Advanced Industrial Economics: Professor Kohei Kawaguchi, Summer 2017

    • Advanced Microeconomics: Professor Norio Takeoka, Spring & Summer 2017

Other fun facts:

  • I passed the Society of Actuaries preliminary exam series in 2015.

  • I was born and raised in Portland, Oregon.

  • I grew up speaking English and Japanese (thanks to my Japanese/English translator parents), and also studied Mandarin Chinese for 6 years in high school and undergraduate.

  • I was formerly a Japanese and Chinese studies major in the University of Pennsylvania College of Arts and Sciences, specializing in gender and sexuality studies.

  • Sometimes I like to make satirical redesigns of school logos, such as for Penn, Wharton, and Columbia Business School.