Background
I'm an economist specializing in industrial organization, econometrics, and data analytics. Currently, I serve as a Data Analyst at the New York State Insurance Fund,
where I develop machine learning solutions and lead analytics initiatives, while also providing independent consulting for healthcare economics projects.
My career bridges economics, data science, and policy analysis, with expertise spanning industrial organization, econometrics, and causal inference.
I completed my Ph.D. in Economics at Northeastern University in 2024, where my dissertation examined competition dynamics, public health policy, and market power
in industrial organization. My fascination with mathematics and logical reasoning has evolved into a practical toolkit combining economic theory with advanced
programming and statistical methods. Below, you'll find highlights of my professional journey, academic research, teaching experience, and technical skillset.
Education
The Ohio State University, Columbus, OH
BSc in Industrial Systems and Engineering Aug. 2012 – May 2016
My passion for mathematics and problem solving led me to pursue a Bachelor's degree in Industrial Systems and Engineering at The Ohio State University.
This provided me with a robust understanding of engineering principles, systems optimization, and the interdisciplinary nature
of engineering and its applications in various industries.
While a senior at Ohio State, I took an Operations Research course which sparked my interest in optimization.
Northeastern University, Boston, MA
PhD in Economics Aug. 2018 – May 2024
With renewed appreciation of the generalizable tools Operations Research and Economics offer, I pursued a Ph.D. in Economics at Northeastern University.
My doctoral studies focused on industrial organization, public policy, and applied econometrics, equipping me with advanced analytical skills and a deep understanding
of economic principles and their real-world applications. My dissertation examined competition dynamics, public health interventions, and market power across three distinct essays.
Professional Experience
New York State Insurance Fund, New York, NY
Data Analyst 2 Apr. 2024 – Present
In my current role at NYSIF, I lead data analytics initiatives that drive operational improvements and cost control:
- Medical Spending Index: Created an index benchmarking medical costs to industry standards, improving cost control and enabling data-driven decision-making for the organization.
- Risk Dashboard: Developed an ML-driven risk-classification dashboard that streamlined the underwriting process, enhancing efficiency and accuracy in risk assessment.
- Team Skill Development: Led biweekly training sessions in econometrics, statistics, and machine learning, upskilling the analytics team and fostering a culture of continuous learning.
- Workflow Automation: Automated key workflows, saving approximately 10 hours per week for a 3-person team, allowing focus on higher-value analytical tasks.
ScioScientific – Kettering Health, Remote
Independent Economist Aug. 2025 – Present
As an independent economist, I provide specialized economic analysis and strategic planning for healthcare technology implementations:
- ROI Plan: Project-managed and authored the system-wide ROI plan for Glucommander expansion across Kettering Health, including severity tier analysis and avoided-event valuation. Applied a matched-counterfactual design using CCR-based costing methodology with comprehensive sensitivity analyses to ensure robust financial projections.
Northeastern University, Boston, MA
Graduate Assistant/Student Aug. 2018 – Apr. 2024
Throughout my Ph.D. program, I balanced teaching and research responsibilities that developed both my technical and mentorship skills:
- Instructor of Record - Master's Econometrics: Delivered instruction on econometric theory and its practical application utilizing RMarkdown, preparing graduate students for applied empirical research.
- Research Assistant:
- Developed the theoretical framework for "Endogenous Maverick Behavior: A Model with Application and Evidence," contributing to the economic theory of competitive firm behavior.
- Matched approximately 3 million households to the nearest accessible ATM using Python and the Google Maps API to augment survey data for financial access research.
- Developed and implemented scripts to collect, clean, and merge controls into 30 years of FBI Uniform Crime Report data for analysis of crime patterns and policy impacts.
- Accessed and integrated Brazil Ministry of Health data with schooling datasets on a remote server, evaluating how mental health facilities affect youth educational outcomes.
- Math Bootcamp Instructor: Taught Linear Algebra, Derivative Calculus, and Statistics to incoming second-year Ph.D. students for three consecutive years, strengthening the foundational quantitative skills essential for doctoral-level economics research.
Harvard University, Cambridge, MA
Teaching Assistant June 2022 – Aug. 2022
Served as a Teaching Assistant for economics courses during the summer session, supporting student learning and course administration.
American Antitrust Institute, Washington, DC
Research Fellow May 2021 – Jan. 2022
As a Research Fellow, I contributed to policy advocacy through economic analysis and research:
- Anticipating the Next Generation of Powerful Digital Players: Helped shape research questions, performed data collection and analysis, and contributed to drafting the final white paper identifying emerging tech companies and competition policy implications.
- Comment to DOJ (Time Warner–Discovery merger): Crafted a comment for the Attorney General rebutting efficiency claims with evidence from prior mergers and economic literature, collaborating with Public Knowledge.
- Comment to DOT (American Airlines-JetBlue): Drafted a comment for the Secretary of Transportation reviewing code-sharing literature and applying insights to the proposed arrangement between American Airlines and JetBlue.
Bentley University, Boston, MA
Adjunct Professor - Intermediate Macroeconomics July 2021 – Aug. 2021
Taught Intermediate Macroeconomics as an adjunct professor during the summer session, marking my first solo teaching experience in higher education.
Lockheed Martin, Syracuse, NY
Manufacturing Engineer - Leadership Development Program July 2016 – Aug. 2017
In my main project at Lockheed Martin, I combined Business Intelligence tools, VBA, and batch scripting to generate reports by product area.
I automated these reports to be sent daily to the inboxes of area managers and displayed them on television screens throughout the facility.
This automation enabled managers to spend less time on report generation while giving them a clear snapshot of the manufacturers' performance.
In my second project, I collaborated with the senior in-house Oracle developer. Together, we addressed a challenge in the building process where numerous
small parts had to be retrieved from a warehouse and assembled into a kit. We designed an application that expedited the collection of these parts and
facilitated the tracking of each piece of equipment throughout the assembly process. This system also accounted for out-of-stock parts, allowing the assembly to commence without them.
I thoroughly enjoyed my time at Lockheed Martin but felt a pull toward acquiring a more versatile toolkit. Drawing from my background in Operations Research and my growing passion for computer science,
I chose to delve into Economics, which I saw as the ideal fusion of these fields.
Federal Reserve Bank of Boston, Boston, MA
Payments Strategies Intern Mar. 2019 – Nov. 2019
During my time at the Federal Reserve Bank of Boston, I contributed to payment system research and analysis:
- 2019 Federal Reserve Mobile Financial Services Survey: Automated survey distribution to over 2,000 financial institutions, cleaned and analyzed responses regarding mobile banking and payment services, and contributed to the published report. Given the sensitive nature of the information, I exclusively used VBA for these tasks.
- Payment Identity & Authentication Fraud: Developed a comprehensive model detailing various types of payment fraud and their corresponding mitigation strategies. Collaborated with and managed an undergraduate intern to review white papers on fraud types and mitigation techniques, then synthesized this information into a clear model presented to financial institutions.
Teaching
Instructor of Record
Master's Econometrics - Northeastern University (Academic Year)
Delivered instruction on econometric theory and its practical application utilizing RMarkdown, preparing graduate students for applied empirical research.
You can explore the lectures for this course here.
Intermediate Macroeconomics - Bentley University (July 2021 – Aug. 2021)
Taught Intermediate Macroeconomics as an adjunct professor during the summer session, marking my first solo teaching experience in higher education.
Math Boot Camp - Northeastern University (2019, 2020, 2021)
Led the week-long intensive Math Boot Camp for incoming second-year Ph.D. students for three consecutive years. Covered topics including
Linear Algebra—whose material you can view or download here—and
Static Optimization, which you can also view or download here.
Teaching Assistant
Harvard University (June 2022 – Aug. 2022)
Served as a Teaching Assistant for Econometrics during the summer session.
Northeastern University (2018 – 2024)
Assisted in a range of courses, including Bubbles, Busts, and Bailouts (a deep dive into the causes and aftermath of the 2008 Housing Crisis),
Intermediate Macroeconomics, Intermediate Microeconomics, Introductory Econometrics, the Capstone course, and Development Economics.
Academic Research
Dissertation
My dissertation, Three essays in applied economics, comprises three distinct chapters examining competition, pricing dynamics, and the intersection of public health policy with criminal behavior. The essays are under embargo until May 2026, per Northeastern University policy.
- Chapter 1: Endogenous Maverick Behavior - This chapter examines the price dynamics observed when a nascent, disruptive firm expands to mirror the stature of an established incumbent. I developed a dynamic model to simulate a firm's pricing strategy as it evolves, predicting an initial phase where the firm disrupts the market with declining prices, followed by a surge in prices as the firm matures. Empirically, this trajectory was evident in the case study of Southwest Airlines.
- Chapter 2: Drug Monitoring and Intimate Partner Violence - Published as Dave et al. (2025) in the Journal of Population Economics, this chapter assesses the impact of mandatory prescription drug monitoring programs on Intimate Partner Violence rates. This work built on my research assistant experience and required developing scripts to collect, clean, and merge controls into 30 years of FBI Uniform Crime Report data.
- Chapter 3: Beef Procurement and Market Power - Inspired by my tenure at the American Antitrust Institute, this chapter investigates the tactics employed by beef processors, specifically how they leverage contractual procurement to influence cattle prices, and whether this trajectory aligns with competitive market behaviors.
Research Assistant Projects
During my Ph.D. program, I worked as a research assistant on several major projects with Professor Bilge Erten, managing both technical implementation and team coordination:
- Mental Health Facilities and Educational Outcomes in Brazil - This research examines the impact of Public Juvenile Mental Health facilities (CAPS) on educational outcomes. Working with healthcare data from Brazil's Ministry of Health and educational data from the Ministry of Education, I helped analyze a dataset encompassing over 3 million children. I matched children with control units using precise matching techniques within an event study framework. For this project, I pinpointed facility geolocations using the Google Maps API; you can view a demonstration of my approach here.
- OxyContin Reformulation and Intimate Partner Violence - As mentioned above, this project resulted in a published paper (Dave et al., 2025) and also served as the basis for my second dissertation chapter. I developed and implemented comprehensive scripts to gather, clean, and integrate controls into FBI crime data.
Publications
- Dave, D., Erten, B., Hummel, D. W., Keskin, P., & Zhang, S. (2025). Fighting abuse with prescription tracking: Mandatory drug monitoring and intimate partner violence. Journal of Population Economics, 38(3), 57.
- Fraser, T., Aldrich, D. P., Panagopoulos, C., Hummel, D., & Kim, D. (2022). The harmful effects of partisan polarization on health. PNAS Nexus, 1(1), pgac011.
- Panagopoulos, C., Fraser, T., Aldrich, D. P., Kim, D., & Hummel, D. (2022). Bridging the Divide: Does Social Capital Moderate the Impact of Polarization on Health?. Political Research Quarterly, 75(3), 875–891.
Programming
Programming for Research
All code samples mentioned above can be found here.
In addition to my primary pursuits, I've embarked on a journey of continuous
learning both out of personal interest and to further hone my technical skills.
I've been self-learning C++, sharpening my SQL skills, and diving deep into general computer
science concepts through LeetCode problems. My progress can be seen on my LeetCode profile
, which is available here.
Furthermore, I'm actively enhancing my understanding of Machine Learning by taking courses on Coursera.
Skills
Technical Tools
Programming Languages & Statistical Software: R, Python, STATA, VBA, SQL
Data Visualization & Analytics: Tableau, Business Intelligence Tools
Documentation & Typesetting: LaTeX, RMarkdown
Economic & Analytical Methods
Econometric Techniques: Econometrics, Causal Inference, Structural Modeling
Economic Theory: Industrial Organization, Dynamic Programming
Data Science: Data Scraping/Mining, Machine Learning
Operations & Optimization: Operations Research, Lean Six Sigma