Data Scientist, Project Success and Innovation

This is a Fully Remote Job About Our Client: The organization operates within the behavioral and social science research sector, focusing on addressing significant challenges through evidence generation and data-driven solutions. It provides technical assistance to expand opportunities and improve lives, operating at national and global levels. About the Opportunity: The DATA SCIENTIST, PROJECT SUCCESS AND INNOVATION, will apply advanced quantitative expertise to support innovation, scaling, and research analytics across multiple project teams. This role contributes to developing and maintaining analytic tools and workflows that enhance operational effectiveness and leads quantitative analyses on research projects, translating technical results into actionable insights for stakeholders. Responsibilities: Build and maintain shared analytic tools, code libraries, project templates, and pipelines. Develop documentation, training materials, and onboarding guides for diverse technical users. Support adoption of new tools by troubleshooting and addressing user feedback. Prototype and assess new tools and platforms, including machine learning and AI applications. Maintain deployed tools through issue triage, bug fixes, and user feedback tracking. Contribute to planning and progress tracking for innovation activities. Conduct quantitative analyses for causal and non-causal research questions. Lead analytic components of studies with senior researcher support. Manage, clean, and quality-assure complex datasets. Build and document reproducible analytic workflows and quality control procedures. Review code from junior staff and support their analytic development. Participate in study design and analytic planning. Draft analytic sections of reports and translate findings for non-technical audiences. Track deliverables and timelines for assigned analytic tasks. Contribute technical content to proposals. Requirements: Master's or doctoral degree in a quantitative field such as statistics, computational social science, education data science, economics, or related disciplines. Coursework or experience in causal inference and statistical modeling. Experience with complex survey data, sampling, and large-scale administrative or linked datasets. Application of quantitative methods to education, health, or social policy. Familiarity with machine learning and AI methods, including large language models. Experience building tools for others and supporting their use. Familiarity with social research data types and restricted-use or confidential data. Experience maintaining code used by others. Proficiency in R and/or Python. Working knowledge of Stata. Familiarity with version control systems (Git, Github) and reproducible research practices. Familiarity with literate programming tools such as Quarto, R Markdown, or Jupyter. Effective communication with diverse technical audiences. Ability to write clearly for non-technical readers. Pay Range and Compensation Package: The pay range and compensation package for this role will be determined based on the candidate's experience, skills, and other relevant factors. Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin. Note: TalentHop is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.