The political R&D group is seeking a Data Scientist to join our team of data scientists and strategists in New York City. We’re a small team who works hard and makes a measurable impact in supporting progressive causes. If you’re looking for a way to have a big impact on the 2020 election, this is it.
We function as the research and development arm for Civis's political work, and we incubate our work directly with some of the largest, most impactful progressive organizations in the country. Problems ranging from large-scale optimization and resource allocation to high dimensional modeling to causal inference make up our day-to-day.
Civis embraces the individuality of our employees and we celebrate each other's differences. Our products, services, and culture benefit from and thrive on the unique perspectives brought by each person in our Civis community. We're proud to be an equal opportunity workplace, and we are committed to equal employment opportunity regardless of race, age, sex, color, ancestry, religion, national origin, sexual orientation, gender identity, citizenship, marital status, disability, or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
As a Data Scientist on the research and development team in our NYC office, your day-to-day work will involve everything from statistical modeling in Python/R, to the testing and development of statistical software and production-level pipelines, to project management. You will also actively work with our strategy teams to distill and communicate results effectively to our progressive clients.
Ability to learn new techniques and technologies quickly as our needs change
Ability to work well in a small team in a self-directed manner
Bachelor’s degree in an analytical subject (political science, statistics, math, economics, physics, etc) or equivalent
Proficiency with machine learning and statistical modeling (e.g., scikit-learn, TensorFlow, Stan)
Familiarity with software development tools and practices (Git, code review, etc.)
Relevant work experience in applied statistics or machine learning