We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Senior Data Scientist at Movement Labs. Movement Labs is an incubator and consulting firm that uses technology, data, and experimentation to stop fascism and build progressive power. We help progressives win and defeat MAGA extremists through year-round work grounded in research and real-world testing. Our team partners with leading advocacy groups, grassroots organizers, and electoral campaigns to develop innovative tactics, win elections, and shift power for the long term.. As the R&D powerhouse for the progressive movement, we’ve run over 100 randomized control trials (RCTs) on voter behavior and helped hundreds of organizations increase their impact. We work hard, and the environment evolves rapidly. We are adaptable, nimble, and shift quickly as needed to meet the moment. We are looking for candidates that thrive in this type of environment.. We seek a Senior Data Scientist to lead analytics work on our Experiments Team.. Our ideal candidate is a fast-mover and knows how to turn data into action. They love digging into tough questions and coming up with answers that drive real change. Meticulous and committed to rigor, our person is relentless about getting the right answer.. As Senior Data Scientist, you’ll solve some of the highest-priority questions in the progressive research community while working alongside one of the most ambitious research teams in the space. When you generate new ideas, we move quickly to implement them; your insights won’t sit on a shelf and will directly shape programs in the field. You’ll play a pivotal role in winning elections up and down the ballot, developing research that impacts the entire progressive ecosystem, and fighting fascism.. This role is fully remote.. Responsibilities:. Develop and lead in-depth analyses of voter file data, survey responses, program implementation data, and other relevant datasets to extract actionable insights and inform strategic decisions. Design creative analytical approaches to answer novel research questions, translating ambiguous problems into rigorous, data-driven solutions. Perform meta-analyses of dozens of randomized controlled trials conducted across multiple election cycles to inform future program design. Collaborate with the Experiments team to design and execute randomized controlled trials (RCTs) aimed at netting Democratic votes and stopping fascism. Evaluate the effectiveness of alternative targeting approaches using existing data, proposing data-driven recommendations for continuous improvement. Develop and implement methodologies to assess heterogeneous treatment effects, providing nuanced insights into the impact of interventions across different voter segments. Build and validate predictive models to enhance the targeting of voter contact programs, optimizing resource allocation and maximizing outreach effectiveness. Visualize and present results of analyses to technical and lay audiences. At least five years of experience with the responsibilities described. Exceptional project management skills, with a proven ability to manage complex analytical projects from inception to completion, ensuring timely delivery of high-quality results. Experience aligning analyses with strategic objectives, using data-driven insights to inform and influence programmatic decisions and long-term planning. Experience with a variety of non-randomized methods for causal inference, such as matching and regression discontinuity designs. Adept at figuring out what data will be needed and organizing data for analysis. Proficiency in building predictive models, including data preprocessing, feature engineering, model selection, and evaluation. Experience designing, executing, and analyzing randomized controlled trials. Required programming experience: SQL and either R or Python. Preferred qualifications:. Expertise and experience in elections, voter contact programs, or voter file data.. Experience with advanced causal inference methods, including heterogeneous treatment effect modeling and machine learning-based approaches. Company Location: United States.