In A Nutshell
Responsible for crafting new data project plans and methodological approaches, strategizing incorporation of outside datasets, and managing the data team along with internal collaborations to maximize impact on policy and practice.
Responsibilities
- While the Senior Data Scientist (Supervisor) will learn from the Project’s previous iterations, the new carceral mortality and morbidity agenda will be a significant expansion for the team.
- As such, in addition to being a core member of our Data Team performing a proportionate share of the Data Team’s work, the Senior Data Scientist (Supervisor) will be responsible for crafting new data project plans and methodological approaches, strategizing incorporation of outside datasets, and managing the data team along with internal collaborations to maximize impact on policy and practice.
- They will also articulate, in consultation with the Project’s Faculty Directors, a strategic vision for the expanded collection, processing, and analysis of carceral morbidity data. The Senior Data Scientist (Supervisor) will supervise the team’s Data Analyst, Data Scientist, Senior Research Scientist, and several student research assistants.
Skillset
- Master’s Degree in Data science, quantitative social science, or related field OR 5+ years working experience as a data or research scientist or equivalent combination of education and experience.
- Substantial research experience.
- Experience planning and executing quantitative research including data collection, cleaning, analysis, and publication.
- Experience working with datasets that include missing, unstructured, and/or incorrect data.
- Experience establishing relationships and working with diverse collaborators (e.g., local advocates, government officials, and journalists) with varying levels of technical literacy.
- Strong organizational skills for project planning, data collection procedures, and complex research activities.
- Proficiency using R or another programming language to manipulate data and draw insights from large, complex datasets.
- Strong writing skills, including experience with peer-reviewed manuscripts.
- Experience using git/GitHub to track tasks and data acquisition processes, and regularly update data on GitHub.
- Experience supervising similarly sized data teams and working with diverse collaborators with varying levels of data literacy.