Data Scientist I

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!

You’re endlessly curious, adaptable, and detail-obsessed in the best way. You love rolling up your sleeves to wrestle messy data into shape, making it clean, usable, and ready to reveal its secrets. You’re excited to learn from seasoned teammates but are also comfortable working independently on well-defined problems from day one.

You thrive in a collaborative, friendly, and nerdy environment where people genuinely love what they do. You chase the thrill of deep focus, appreciate your teammates’ brainpower, and hunger for the rush of solving problems no one else has dared to tackle. These are the kinds of challenges that stay with you—in the shower, as you fall asleep, tugging at your brain in the best possible way.

You’re interested in politics, and the ways in which public opinion is created and shaped. You understand the power of narratives to shape the world around us, and want to play a part in the high-stakes, real-world battle over hearts and minds. 

Most importantly, you bring humility, patience, and a commitment to detail. You bring focus and efficiency to your work, knowing when to go deep and when to ship ‘good enough.’ You see this role as a chance to sharpen your craft, learn fast, and make a real contribution to high-stakes, real-world problems.

At Tavern Research, we’re building models to understand and influence how people form opinions online. That means taking on problems like tracing how narratives spread through social platforms, or analyzing how different messages land with different audiences. The data is messy, the questions are ambiguous, and the stakes are high.

As a member of the Data Science team, your role is to help make this work possible. You’ll dive into raw, noisy datasets to clean, structure, and prepare them for analysis. You’ll run exploratory analyses to surface patterns, build features, and support experiments. You’ll contribute to modeling tasks end-to-end, helping turn difficult, open-ended questions into tangible, testable results. While you’ll collaborate closely with senior modelers, we expect new hires to ramp quickly and take ownership of clearly scoped modeling and data tasks.

From day one, you’ll be hands-on with real-world data and problems that matter. You’ll have support from senior team members, but you’ll also be expected to bring rigor, patience, and persistence to your work. Over time, as your skills deepen, you’ll have opportunities to take ownership of increasingly complex modeling projects, building toward the point where you can design and lead experiments yourself.

• →Work hands-on with real-world, unstructured data: cleaning, debugging, and engineering features that support effective models.
• →Support the design and execution of numerical experiments by handling data prep, fitting models, and running standard analyses.
• →Contribute to feature engineering and model building, taking ownership of clearly defined components of modeling projects.
• →Write clean, well-documented Python code using standard data science libraries.
• →Assist with model evaluation, diagnostics, and performance monitoring.
• →Collaborate with researchers and engineers to scope and execute tightly defined tasks.
• →Learn and apply best practices and emerging tools in machine learning, AI, and causal inference.
  
  

We know it’s rare to check every box. If you meet most of these, we encourage you to apply:

• This role is designed for early-career candidates with 0–3 years of experience or equivalent hands-on project work who are eager to grow into more advanced modeling responsibilities.
• Strong academic or applied background in data science and software engineering or  closely related fields.
• Experience building statistical models (beyond differential equations or simulations).
• Demonstrated experience working with messy, real-world datasets.
• Proficiency in Python and standard data science libraries.
• Familiarity with AI and machine learning concepts like embeddings, supervised and unsupervised ML methods, and agentic systems
• Clear understanding of the data science concepts behind work you’ve done (not just “I ran the code”).
• Strong communication skills and a collaborative mindset
• Humility, patience, and attention to detail.
• We especially value candidates who have independently built data or modeling projects outside of coursework, including internships, research, or production data work.
• Bonus: exposure to model deployment, large language models, or causal inference.

To be explicit: you don't need a degree to work here. You just need to be exceptional at what we're asking from you.