Eric M. Aldrich

• ealdrich@gmail.com
• https://ealdrich.com
• https://www.linkedin.com/in/ealdrich

Summary

Leader in Data Science and Analytics with expertise ranging from technical modeling, to causal inference, experimental design, and analytics reporting to executive leadership. Prior to my full-time transition to tech, I was an academic Economist publishing research in financial econometrics, market design, and experimental economics while consulting in Finance and Data Science.

Experience

• Airbnb, New York, NY

  • Technical Lead Manager & Staff Data Scientist, May 2022 - Present
    • Leading a team of data scientists, analyists, and data engineer to develop, deploy and measure Airbnb pricing products
    • Team stewardship: ML and econometrics modeling, success metrics, experimental design and reporting, (observational) causal analysis, and strategic insights for Product and Finance
    • Embedded with Product, Engineering, and Design to launch multiple pricing features annually
    • Close collaboration with Finance to define success (both short-term and long-term) and report roadmap and OKR results to Executive Leadership
    • Responsible for company-wide host experimentation design and reporting for bi-annual launches

• Amazon, New York, NY

  • Senior Economist, Supply Chain Optimization Technologies (SCOT), Jul 2020 - May 2022
    • Developed topline forecasting models for supply chain capacity and planning
    • Estimated the impact of macroeconomic events on Amazon growth
    • Estimated the impact of wage changes on operational efficiency and topline growth

• Figure Technologies, San Francisco, CA

  • Director, Data Analytics, Sep 2019 - Jul 2020
    • Responsible for firm-wide experimentation agenda
    • Responsible for marketing, product, credit, and finance analytics

• Fulcrum Asset Management, London, England

  • Research Economist, Sep 2017 - Sep 2019
    • Developed dynamic factor model for volatility targeted portfolios
    • Designed framework for option-implied volatility term structure estimation

• Turner, Inc., Atlanta, GA

  • Lead Data Scientist, Dec 2015 - Aug 2017
    • Developed content recommendation system for linear television content and the universe of Nielsen respondents
    • Implemented statistical model to determine the elasticity of audience tune-in to promotional content, identifying opportunities to save ad inventory (10m+ USD/yr)

• Carlyle Group, New York, NY

  • Systematic Trading Consultant, Jan 2014 - Dec 2014
    • Designed systematic rules for hedging large equity portfolios with volatility derivatives

• Effex Capital, Jersey City, NJ

  • Systematic Trading Consultant, Feb 2013 - Jan 2014
    • Constructed optimal combination of order book signals to improve market making strategy in retail FX pools at the 1-minute horizon

• Federal Reserve Bank of Atlanta, Atlanta, GA

  • Economist, Aug 2010 - Aug 2012
    • Developed model to asses the impact of belief dispersion on asset market trading
    • Assessed the macroeconomic impact of Fed policy while constraining nominal interest rates at the zero bound

Academic Experience

• University of California, Santa Cruz, Santa Cruz, CA

  • Associate Director, Center for Analytical Finance, Oct 2017 - Sep 2019
    • Oversight of budget, allocation of resources to research, curriculum design, and workshops on topics surrounding market design and systematic risk
  • Assistant Professor, Department of Economics, Jul 2012 - Sep 2019
    • Led research team conducting financial market design experiments at the UCSC LEEPS Lab
    • Taught time series econometrics (Ph.D.), finance (M.S., B.S.), advanced econometrics (B.S.)
    • Research areas: financial econometrics, market design, market microstructure, computational macro

Education

• Ph.D. in Economics, Duke University, December 2011
• M.S. in Statistics, University of Washington, June 2005
• B.S. in Economics, Duke University, May 2002

Software/Languages

• Statistical Computing and Scripting: Python, R, C++, CUDA, Matlab
• Cloud Computing: GCS, Unix/Linux (shell scripting), Docker, AWS
• Data Management/Retrieval: BQ, SQL, REST
• Version Control: Git, Mercurial

Awards

• Gerald P. Dwyer Prize, Society for Nonlinear Dynamics and Econometrics, Mar 2011
  • Awarded top paper in Finance for “Computational Methods for Production-Based Asset Pricing Models with Recursive Utility”
• Alix Family Graduate Fellowship, Duke University, Summer 2009
• 2009 Student Travel Award, Business and Economic Statistics Section, American Statistical Association, Aug 2009
• Hubert M. Blalock Fellowship, Center for Statistics and the Social Sciences, University of Washington, Sep 2002 - Jun 2003

Publications

1. Aldrich, Eric M. and Daniel Friedman (2022), “Order Protection through Delayed Messaging”, Management Science, forthcoming.

2. Aldrich, Eric M. and Howard Kung (2019), “Computational Methods for Production-Based Asset Pricing Models with Recursive Utility”, Studies in Nonlinear Dynamics and Econometrics, 25(1), 20170003.

3. Aldrich, Eric M. and Kristian López Vargas (2019), “Experiments in High Frequency Trading: Comparing Two Market Institutions”, Experimental Economics, 23(2), pp. 322-352. (Online Appendices).

4. Aldrich, Eric M., Kristian López Vargas and Hasan Ali Demirci (2019), “An oTree-based Flexible Framework for Financial Market Experiments”, Journal of Behavioral and Experimental Finance, 30, 100432.

5. Aldrich, Eric M. and Seung Lee (2018), “Relative Spread and Price Discovery”, Journal of Empirical Finance, 48, pp. 81-98.

6. Aldrich, Eric M., Indra Heckenbach and Gregory Laughlin (2016), “A Compound Duration Model for High-Frequency Asset Returns”, Journal of Empirical Finance, 39(A), pp. 105-128.

7. Aldrich, Eric M. (2014), “GPU Computing in Economics”, Handbook of Computational Economics, Vol. 3, eds. Schmedders, Karl and Judd, Kenneth L., Amsterdam: North-Holland, chap. 10, pp. 557-598.

8. Aldrich, Eric M. and A. Ronald Gallant (2011), “Habit, Long Run Risks, Prospect? A Statistical Inquiry.”, Journal of Financial Econometrics, 9(4), pp. 589-618.

9. Aldrich, Eric M., Jesús Fernández-Villaverde, A. Ronald Gallant and Juan F. Rubio-Ramírez (2011), “Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors”, Journal of Economic Dynamics and Control, 35, pp. 386-393.

10. Gneiting, T., K. Larson, K. Westrick, M. G. Genton, and E. Aldrich (2006), “Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching Space-Time Method”, Journal of the American Statistical Association, 101, 968-979.

11. Aldrich, Eric M., Peter Arcidiacono, and Jacob L. Vigdor (2005), Do People Value Racial Diversity? Evidence From Nielsen Ratings”, The B.E. Journal of Economic Analysis & Policy, 5(1), pp. 1-22.

Working Papers

1. Aldrich, Eric M., Joseph A. Grundfest and Gregory Laughlin (2017), “The Flash Crash: A New Deconstruction”, Working Paper.

2. Aldrich, Eric M. (2013), “Trading Volume in General Equilibrium with Complete Markets”, Working paper.

3. Aldrich, Eric M. (2005), “Alternative Estimators of Wavelet Variance”, Master’s Thesis, Department of Statistics, University of Washington, Seattle, WA.

4. Handcock, Mark S. and Eric M. Aldrich (2002), “Applying Relative Distribution Methods in R”, Working Paper no. 27, Center for Statistics and the Social Sciences, University of Washington.