Data Scientist
verasightPortland (ME)
About the role
What we are looking for:
Verasight is building the future of survey research with unparalleled data quality and a re-imagined respondent experience. Our team recognizes the importance of high-quality data for our customers to make key decisions that affect national policy, academic research, the direction of Fortune 500 companies, and important public conversations. We are looking for a Data Scientist to help us expand our capacity to field high quality surveys for our clients. This role will apply and expand Verasight’s code base to execute rigorous and replicable data collection, analysis, quality control, and reporting methods. We are a scrappy team and you will have an opportunity to help expand access to high quality survey data. We depend on colleagues who are diverse, team oriented, novel thinkers, and passionate about redefining the data landscape. Verasight works to create a welcoming community in which all individuals are respected and included. Meet the Verasight team here: https://www.youtube.com/watch?v=WC3Zx3TKZzcHow to ApplyDoes this position sound like a good fit? Email us at Include this role's title in your subject line (it'll help us to sort through the emails) Include your CV/Resume, a one-paragraph statement of interest, and a link to your GitHub profile (if available)
Responsibilities:
Leverage Verasight’s data pipelines and processing procedures to own the data collection and quality process from end to end, including: building contact lists and sampling frames, monitoring survey fielding, cleaning and analyzing survey response data, writing methodology documentation, and preparing client deliverables Manage multiple simultaneous projects throughout all stages of the project life cycle, identifying potential roadblocks early and proactively proposing solutions Contribute, in collaboration with the Verasight team, innovative methods of automation and expand the data science team “toolbox” to suit a wide variety of data needs Conduct internal experimentation and research to hone Verasight’s approach to survey research Bring a creative and solutions-oriented mindset
Required Qualifications:
- Experience coding in R, including writing custom functions, package development, REST API integration, and writing reusable and well documented code
- Enthusiasm for bringing AI tools (such as Claude Code) to survey research
- Knowledge of quantitative survey research methodologies, statistical concepts, and the ability to apply them to solve novel problems
- Innovative, independent mindset and a willingness to learn new technical and statistical skills when needed to tackle emerging challenges
- Strong communication skills to suit a highly-collaborative fast-paced remote work environment
- Experience managing multiple ongoing projects with competing deadlines
- Commitment to working in an inclusive environment
Preferred Qualifications:
- Experience with commonly used survey software platforms, such as Qualtrics
- Familiarity with GitHub for collaborative code development
- Practical experience using voter file data (e.g., L2, Catalist, TargetSmart)
- Knowledge of survey weighting practices, including population benchmark data (e.g., Census) and poststratification techniques (e.g., raking)
- Experience writing SQLFamiliarity with JavaScript 2+ years of survey or social science research experience
Benefits:
- Competitive salary based on experience
- Health insurance 401k with company matching
- Opportunity to travel to represent Verasight at conferences
- Gain experience working directly with government agencies, nonprofits, academic researchers, and corporations
- Remote work
About Us:
Founded by Peter Enns (Cornell Professor of Government & Public Policy) and Ben Leff (Stanford GSB and ex. Goldman Sachs), Verasight was built by and for academic researchers. Our customers include national media organizations, Fortune 500 companies, national and state government agencies, investors, brands, and researchers. We are looking for bold leaders to join our team to re-invent what it means to collect and analyze survey data.
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