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Blue Rose Research is seeking a Machine Learning Scientist to join our Scaled Polling & Forecasting Team. We build and maintain models that help progressive organizations understand the electoral landscape and make informed decisions.
The role covers the full modeling lifecycle from raw survey data to predictive scores, requiring rigorous statistics and good judgment under uncertainty. You’ll work with engineers, statisticians, and political analysts on impactful projects.
Note: We are currently collecting resumes for this role; active hiring will begin in December. Details of the role may be revised when hiring begins.Blue Rose Research
develops cutting-edge products used by the most important progressive organizations in the country. Our research informs short- and long-term strategy for advancing progressive causes and has a trusted track record among key decision makers.We're a fast, dynamic team shipping innovative work that evolves week by week. We're looking for someone who brings passion for machine learning, sharp attention to detail, and a drive to make an impact – sometimes under tight timelines.Public examples of our work
David Shor's conversation with Ezra Klein in the New York Times analyzing the 2024 election is the best public window into how we think.How Democrats Will Run on the GOP's Tax Bill : the Democratic Congressional Campaign Committee’s and Democratic Senatorial Campaign Committee’s shared memo on how Blue Rose’s research is informing their campaign communications.Bernie Sanders on AI job loss : Senator Sanders cites Blue Rose polling while talking about voters’ fears of AI causing job loss.
We're hiring a Machine Learning Scientist to join our Scaled Polling & Forecasting Team, the group responsible for Blue Rose's flagship electoral work. Our team builds and maintains models that help progressive organizations understand the electoral landscape and make informed decisions. We track public opinion, forecast races across the ballot, develop resource allocation tools, and deliver analysis that campaigns and allied organizations rely on to set strategy. Our problems are not well suited to off-the-shelf ML solutions: we work with messy, evolving political data and constantly pressure-test our accuracy against real election outcomes. The role spans the full modeling lifecycle from raw survey data to predictive scores and requires both rigorous statistical thinking and the judgment to know when a number is real versus an artifact.
Specifically, you'll:
This is a remote or in-person optional position. We have an office in New York City and a number of team members who work in-person regularly. Our teams work on mostly East Coast hours.