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.

Requirements

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.

Benefits

Movement Labs maintains a transparent salary structure with clear levels of advancement.
Excellent health, dental, and vision benefits.
401(k) matching.
Unlimited Paid Time Off.
This position is eligible for the collective bargaining unit.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

data analysispredictive modelingcausal inferencefeature engineeringmodel selectionmodel evaluationrandomized controlled trialsdata preprocessingSQLR

project managementstrategic alignmentdata-driven decision makingproblem solvingcommunication