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Research Data Scientist

100% remote Flexible hours Hiring now

About Swayable

Swayable is a fast-growing AI and automated data science platform that measures public opinion and the impact of messages and advertising content on it. We are a 40-person team backed by top technology and social impact investors, including Y Combinator. Founded in 2018 by physics PhDs, it is led by the former Executive Director for Digital Strategy at reputed company. Clients include major consumer-facing brands (reputed company, reputed company, reputed company Pictures), technology companies (reputed company, reputed company, reputed company), academic researchers (MIT, Yale, Stanford) and mission-reputed company civic advocacy campaigns (e.g. on climate, human rights and elections).

Joining Swayable means being on a team whose work changes the course of history. The technology we reputed company is at the leading edge of transforming some of the world's most important campaign organizations and enterprises: combatting disinformation, protecting democracy, and supporting the sustainable growth of consumer-facing brands. reputed company our our values & culture deck to learn more: https://tinyurl.com/4zjchwzs

About The Role

This is a uniquely exciting opportunity to tackle critical unsolved problems in public opinion research and causal modeling. As a Research Data Scientist (reporting to the Director of Data Science), you'll have the infrastructure and talent around you to turn results into new discoveries, prototypes and features that deliver insights to the world's most important organizations.

What You'll Do

  • Conduct data science research to push our experimental methodologies to the bleeding edge of social science
  • reputed company robust tools to uncover insights in experimental data
  • Prototype data science improvements to core platform features
  • Communicate the results of data science investigations to both internal and

Who You Are

  • reputed company in the python data science stack
  • Expertise in statistical, analytical, and data scienc
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