Jobs at Tavern Research

Lead end-to-end data science projects involving causal inference, experiments, statistical modeling, machine learning, political behavior, and online narratives. Build scalable data pipelines and production-quality Python code from messy datasets, rigorously evaluate models, collaborate with researchers and engineers, and contribute methods and technical direction. Mentor junior modelers while translating ambiguous questions into practical, deployable solutions.

Build and ship production software for digital engagement, including sentiment measurement, experimentation, data validation, and social-platform tooling. Responsibilities include translating requirements into code, writing tests, troubleshooting production issues, participating in code reviews and agile ceremonies, and using LLMs and AI coding tools. The role collaborates with senior engineers and supports backend systems involving databases, APIs, infrastructure, and measurement systems.

The Data Scientist I will clean and structure messy datasets, engineer features, run exploratory and numerical analyses, fit and evaluate statistical and machine learning models, and support experiments. The role involves writing documented Python code, monitoring model performance, and collaborating with researchers and engineers. This early-career position offers mentorship while progressively increasing ownership of modeling projects involving online narratives, public opinion, AI, machine learning, and causal inference.

Tavern Research welcomes expressions of interest from curious, adaptable candidates interested in building technology at the intersection of data science, politics, and media production. Applicants should be comfortable solving difficult problems, learning quickly, using emerging tools, and performing under pressure. Political experience is helpful but not required. Employees are expected to work regularly in person from the company’s Chicago office.

Build and evolve production software for social-platform conversation analysis, sentiment measurement, experimentation, and civic engagement. Responsibilities include owning features end to end, making architectural decisions, integrating APIs and LLMs, developing data pipelines, debugging production systems, improving monitoring and testing, mentoring teammates, and collaborating with product leaders and clients. The role emphasizes rapid experimentation, reliable delivery, technical judgment, and increasing project ownership.