Tech companies are increasingly choosing to hire PhD students in Economics.
I read an article about the Economics Team at Instacart, and here are my takeaways.
Projects they worked on
The economists at Instacart, part of their Econ Team, work on a variety of challenging projects that blend economics with machine learning.
- Optimized Bidding for Ad Auctions:
- Economic Understanding: The team applied their knowledge of ads incrementality, auction formats, and auction pressure to develop a comprehensive understanding of the ads marketplace.
- Technical Solution: Developed an algorithm for optimized bidding, tailored for a high-volume, latency-sensitive environment, offering flexible and effective bidding options for advertising partners.
- Impact and Collaboration: Worked closely with the Ads team, achieving strong results and providing significant value to advertising partners through this initiative.
- Contextual Bandit Algorithms for Incentive Targeting:
- Economic Analysis: Utilized econometric methods to estimate heterogeneous treatment effects and optimize trade-offs between different business metrics.
- Model Development: Created both batch inference and real-time inference models, integrating them into the system for effective upsell placement.
- Production Integration: Ensured the models were production-ready, aligning them with Instacart's operational environment and achieving practical utility in a real-world setting.
- Causal Inference and Experimental Design:
- Long-term Outcome Measurement: Used surrogate models to measure long-run outcomes, demonstrating the capacity to understand and predict extended impacts of various initiatives.
- Natural Experiments: Leveraged natural experiments for experiment design, including treatments inspired by regression discontinuities, showcasing innovative approaches to problem-solving.
- Non-randomized Treatment Effects: Estimated causal effects of treatments like Instacart+ membership and developed customer segments for enhanced model inputs and experimental analysis, contributing significantly to understanding customer behavior and preferences.
Their Value as Economists:
- Holistic Problem-Solving Approach: Merging economic theory with machine learning to tackle complex, multidimensional problems, providing end-to-end solutions.
- Efficient and Effective Solution Development: Rapid development and deployment of solutions, facilitated by the dual expertise in economics and technology, showcasing a streamlined process for handling complex, data-intensive tasks.
- Insight into Economic Principles and Causal Inference: Profound grasp of economic theories and causal relationships, driving data-centric decision-making and refining experiment designs for improved outcomes.
- Versatility and Adaptability: Cross-functional capabilities, enabling work across diverse product areas and problem types, adding a unique, interdisciplinary perspective to traditional tech roles, and catalyzing innovation and growth.