Tavern Research is a political tech startup that builds tools and insights to help our customers win elections and make better decisions. We specialize in scaling expert human work, like content generation and survey research. We're a venture-backed, mission driven, fast-moving, mostly technical team focused on supporting winning campaigns. Everything else is on our website. If you still have questions, let us know when you apply!
About You
You’re endlessly curious, unusually adaptable, and a little obsessive—in a good way. You think influence is a math problem (but also a media problem, a language problem, and a sociology problem). You think in systems, but know how to zero in on the one weird data point that doesn’t fit. You go down rabbit holes, snap out of them when needed, and return with something useful.
You’ve probably spent a few too many hours in a notebook trying to squeeze a little more signal out of noisy data. You have strong opinions about evaluation metrics, but you’re not precious when the problem demands pragmatism. You care deeply about the quality of your work and know when “good enough” is the right call.
You’re excited to be part of a collaborative, friendly, and nerdy environment where people genuinely love what they do. You’ll relish the intense flow states, appreciate your teammates, and hunger for the highs of solving problems no one else has dared to tackle. These are the kinds of problems that grip you—in the shower, as you fall asleep, tugging at your brain in the best possible way.
About the Role
Dynamic systems are hard to model. Dynamic systems involving human behavior, especially when interactions aren’t directly observable, are even harder. But the stakes are too high not to try.
At Tavern Research, we're building models to understand and influence how people form opinions online. You’ll take on problems like identifying bot networks, tracking the spread of narratives, modeling how media exposure shapes political attitudes, and helping campaigns test and target their messaging more effectively. Some days, you’ll design experiments. Other days, you’ll parse engagement metrics and raw text to figure out what’s actually working and why.
We believe people’s beliefs are shaped by the information they consume, and that information is increasingly engineered. The internet cracked the door open for opinion manipulation, and language models kicked it wide open. If we care about the future of democracy, we need to understand how influence spreads, mutates, and lands, and help our partners respond with precision and speed.
You won’t be handed a clean dataset or a fully formed research question. You’ll help define the problem, shape the data, and build tools that turn ambiguity into real-world impact.
One week, you might build a discriminator to detect bot networks. Another, you might model the impact of different messages in noisy, fast-moving attention markets. Or, develop a custom embedding model to track evolving narratives.
You’ll work closely with a tight-knit, interdisciplinary team, testing ideas fast, shipping iteratively, and pushing toward real-world impact. The timelines are tight, the inputs are messy, and the problems are wide open. If that sounds thrilling, we encourage you to apply.
We value in-person collaboration and expect employees to work regularly from our Chicago office.
Responsibilities
Design and analyze experiments to measure treatment effects. You’ll collaborate on experiment design, analyze results independently, and iterate using methods like randomized trials, difference-in-differences, and causal inference.
Build and maintain statistical and machine learning models that generate political and behavioral insights.
Work hands-on with messy, real-world data: cleaning, debugging, and engineering features that support effective models.
Write clean, well-documented Python code using scientific computing libraries.
Partner with researchers and engineers to turn complex questions into technical solutions and modeling approaches.
Contribute to model evaluation, diagnostics, and performance monitoring.
Stay up to date on best practices and emerging tools in machine learning, AI, and causal inference.
Qualifications
We know it’s rare to check every box. If you meet most of these, we encourage you to apply:
Experience in a technical or data science roleStrong proficiency in Python and widely used data science libraries
Experience working with real-world, messy datasets
Familiarity with machine learning techniques like sentiment analysis, topic modeling, or network analysis
Experience with causal inference, experimentation frameworks, or statistical modeling
Exposure to large language models or experience integrating them into workflows is a plus
Strong communication skills and a collaborative mindset
Comfort with version control and modern engineering workflows
To be explicit: you don’t need a degree to work here. You just need to be good at the things we’re asking from you.
Benefits
Premium health insurance
Unlimited PTO
Office closed for all federal holidays
401k match
Equity
Tavern Research is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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