Data Scientist II — Causal ML & Production Modeling

Tavern Research:
Data Scientist II LOCATION

Chicago, IL, 60606

$150000 - $179000 (Yearly)

Employer-sponsored health insurance offered

Python, R

Tavern Research

Data

Other

Departmental Staff (a role in a specific department. Ex: Organizer, Finance Assistant, Social Media Manager)

Data Scientist II

Location:

Chicago, IL

Office: 3 days/week in South Loop office

Reports to:

Chief Technology Officer (CTO)

About Tavern Research

Tavern Research is a political tech startup building tools and insights to help our customers win elections and make better, evidence-based decisions. We specialize in scaling expert human work, such as content generation and survey research to support thoughtful, data-driven civic engagement. We're a venture-backed, mission-driven, fast-moving, and mostly technical team focused on supporting campaigns and organizations working to strengthen democratic participation.

We are experimental by design and expect every team member to continuously improve how they work using new tools and technology. Everything else is on our website. If you still have questions, let us know when you apply!

About You

You bring intellectual horsepower and deep modeling experience. You don’t wait for a clean dataset. You know how to find the signal in noise and can design solutions that hold up under scrutiny. You’re motivated by impact and you want to see your models tested against the real world and sharpened by fast feedback cycles. You’re comfortable taking ambiguous problems and independently shaping them into modeling approaches that can be tested and deployed.

You’re generous with your expertise, able to support teammates and mentor junior modelers, while staying deeply hands-on with the work yourself. Above all, you combine technical depth with pragmatism. You know when to chase the perfect solution and when “good enough” will move the mission forward faster.

You’re fascinated by politics, and by how narratives and public opinion are formed and spread. You’re drawn to the challenge of understanding and shaping ideas that move people and influence the direction of public life.

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.

As a Data Scientist II, you’ll take on substantive projects end-to-end, defining the problem, shaping the data, and designing models that bring clarity to messy, high-impact questions. Your work may include tracking the spread of narratives, modeling how media exposure shapes political attitudes, or developing custom embedding models to follow evolving discourse. Some days you’ll be designing experiments; other days you’ll be debugging noisy datasets or parsing engagement metrics 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. Instead, you’ll be expected to bring both scientific rigor and creativity to ambiguous, open-ended problems. You’ll collaborate closely with a tight-knit, interdisciplinary team, testing ideas fast, shipping iteratively, and pushing toward real-world impact. While your primary focus will be hands-on modeling, you’ll also support and mentor junior modelers, helping to expand Tavern’s technical depth and build a sustainable senior–junior structure.

This is a role for someone who thrives at the edge of research and application, where the data is messy, the problems are wide open, and the answers matter.

We value in-person work and expect employees to work regularly…