• Lead and develop a team of senior data scientists. You'll set direction, run planning and standups, give honest feedback, and help each person grow.
• Own the team roadmap with senior leadership, prioritizing the work that most improves what strategists and campaigns actually get from our products.
• Set the bar for what "good" looks like for our AI systems, and build the evaluation infrastructure to measure it: eval sets, human labeling, and LLM-as-judge pipelines.
• Lead the training and calibration of judge models, making sure they track expert human judgment and stay reliable as products and underlying models change.
• Build systems that use those judges to automatically optimize context (prompts, retrieval, examples, and agent workflows), so quality improves continuously instead of through hand-tuning.
• Guide decisions about when to use off-the-shelf models, when to fine-tune open-weight models, and how to get them into production.
• Keep the team's model work connected to the product by partnering with engineering and political strategists on how real users interact with what we build.
• Balance rigor with pragmatism, making clear tradeoff calls when a real deadline and a real user are on the line.
• Communicate results and tradeoffs clearly to technical and nontechnical audiences, including in client-facing settings.