Research Data Scientist

The Research Data Scientist serves as the Center for Crime, Urban Research & Education’s lead quantitative analyst, providing advanced statistical expertise to support research, evaluation, and data-driven decision-making. The position is responsible for managing complex datasets, conducting statistical analyses, developing analytical models, and translating findings into actionable insights related to crime, public safety, urban issues, and community well-being., * Designs and conducts advanced statistical analyses using quantitative research methods, including regression, multivariate analysis, predictive modeling, and longitudinal analysis.

• Collects, cleans, validates, merges, and manages large datasets from police, criminal justice, public safety, governmental, and community sources.
• Develops statistical models, dashboards, data visualizations, and performance metrics to support research studies and program evaluations.
• Prepares technical reports, research summaries, policy briefs, and presentations that communicate findings to academic, governmental, and community audiences.
• Collaborates with faculty, researchers, students, and external stakeholders in study design, methodology development, and interpretation of findings.
• Provides statistical consultation and methodological guidance for grant-funded projects and externally sponsored research.
• Ensures data quality, integrity, confidentiality, and compliance with applicable research and data governance requirements.
• Assists with grant proposal development, project reporting, and special initiatives supporting C-CURE’s mission.

MARGINAL DUTIES

• Perform other duties as assigned, * Work is performed in a typical interior work environment which does not subject the employee to any unpleasant elements.
• Individual has discretion in relation to walking, standing etc., and has minimal exposure to physical risks.
• Ability to lift up to 40 lbs.

• Statistical theory and applied quantitative methods.
• Research design and program evaluation methodologies.
• Predictive analytics and forecasting techniques.
• Data management and database structures.
• Data visualization principles and reporting techniques.
• Research ethics, confidentiality, and data security practices.
• Criminal justice and public policy research concepts

Skills:

• Advanced proficiency in statistical software such as R, SAS, Stata, SPSS, Python, or equivalent analytical tools.
• Data cleaning, transformation, and validation.
• Statistical modeling and hypothesis testing.
• Data visualization using Tableau, Power BI, R, Python, or similar platforms.
• Technical writing and report preparation.
• Presentation and communication skills.
• Project management and organization

Abilities:

• Applies complex statistical techniques to real-world policy and research questions.
• Interprets and communicates technical findings to diverse audiences.
• Independently plans and executes analytical projects.
• Identifies trends, patterns, and relationships within large datasets.
• Maintains accuracy while managing multiple concurrent projects.
• Handles sensitive and confidential information with discretion.
• Works collaboratively with interdisciplinary teams and external partners., * Master’s degree in Statistics, Biostatistics, Data Science, Economics, Applied Mathematics, Quantitative Sociology, Criminology, Public Policy, or a closely related field., * Minimum of three (3) years of professional experience performing statistical analysis, quantitative research, program evaluation, or applied data science.
• Experience working with large and complex datasets.
• Experience presenting statistical findings to both technical and nontechnical audiences., * Doctoral degree in Statistics, Data Science, Criminology, Public Policy, Economics, or a related field.
• Experience analyzing criminal justice, law enforcement, corrections, courts, public health, education, or urban data.
• Experience supporting or participating in grant-funded research projects.
• Experience with Geographic Information Systems (GIS) and spatial analysis techniques.
• Record of scholarly publications, technical reports, evaluation studies, or applied research products.
• Experience working in a higher education institution, research institute, government agency, or similar research-focused environment.