David Lindsay

David Lindsay

Data Scientist II



I am a Data Scientist at Gopuff with several years with of expierence in Economics and causal inference techniques. At Gopuff I have spent two years working in a production environment, developing experimentation platforms, estimating long-term customer value, providing demand forecasts, and evaluating marketing and loyaty programs. Prior to working at Gopuff I recieved a PhD in Economics from UCLA

Download my resumé.

  • PhD in Economics, July 2022

    University of California, Los Angeles

  • MA in Economics, 2017

    University of California, Los Angeles

  • BA in Mathematics and Economics, 2016

    Trinity College Dublin


Gopuff - Data Scientist II - July 2022 - Present

  • Went from 0-to-1 developing an end-to-end in-house switchback platform, performing all tasks from registration to analysis. Built the front-end using Streamlit deployed using Docker on Azure, results provided as an Mlflow dashboard.
  • Create a full test suite & provided education for the switchbacks platform permitting non-DS create switchbacks. Over 150 switchbacks were registered on the platform, acting as an important part of reducing delivery costs.
  • Using double machine learning and surrogates to create the first long-term value (LTV) model of customers. LTV results were automatically provided with A/B tests. Also created LTV as a service allowing DS to determine customer high-value actions.
  • Assisted with design and elasticity measurement for geographic pricing. Lead to $21 million in incremental margin with little order impact through geographic price discrimination.
  • Used diff-in-diff & synthetic control analysis to evaluate the cost of user acquisition from marketing spend.

UCLA - Research Assistant - 2017 - 2021

  • Assisted with empirical projects economics projects, responsible for data sourcing, data cleaning, creating graphs, and analysis.
  • Developed the key empirical models using linear, panel, and logistic regression, paper published in 2020.


Job Market Paper

  • The Heterogeneous Effect of Local Land-Use Restrictions Across US Households. Abstract: Using a structural approach, I quantify the effect of land-use regulations on different age and education groups. Building on the seminal work of Roback (1982) I estimate a dynamic spatial structural equilibrium model of household location choice, local housing supply and amenity supply. I show that in the long-run, removing land-use restrictions benefits all household groups and increases aggregate consumption by 7.1%. These consumption gains vary across households, less educated and younger households see increases in consumption about twice as large as more educated or older households. In contrast, in the short run, removing land-use regulations reduces the consumption of older-richer homeowners while increasing the consumption of younger renters. In a counterfactual 1990-2019 transition abolishing land-use regulations reduces the consumption of households born before the mid-1960s, while increasing consumption of more recent generations. Given the difficulty in reforming land-use regulations, I explore whether a shift to remote working or creating new urban areas leads to similar consumption gains compared with removing land-use restrictions. Qualitatively I find the gains are similar, but quantitatively are only about 20% as large as abolishing land-use regulations from existing urban areas.


Work in Progress

  • Trading Relationships in the US Corporate Bond Market
    (with Diego Zúñiga)



  • Econ 106F: Finance (UCLA Summer 2019 and Summer 2020).

Teaching Assistant

  • Econ 1: Introduction to Microeconomics (UCLA - Winter 2018)
  • Econ 2: Introduction to Macroeconomics (UCLA - Winter 2020)
  • Econ 101: Intermediate Microeconomics (UCLA - Fall 2018)
  • Econ 102: Intermediate Macroeconomics (UCLA - Fall 2017, Spring 2018, Winter - Fall 2019, Winter 2021, Spring 2021)
  • Econ 103: Econometrics (UCLA - Summer 2021)
  • Econ 106F: Finance (UCLA - Fall 2020, Spring 2020)