CJR Data Science & Forecasting Assistant - College of Health & Human Services

The Center for applied research is seeking a motivated PhD student in Data Science to support ongoing projects focused on data-driven forecasting and spatial analysis. This position is ideal for individuals interested in applying advanced analytical techniques to real-world problems involving large, complex datasets. Career Readiness Competencies Maintain a positive, growth-oriented mindset when facing challenges. Actively listen and respond respectfully in meetings and conversations. Identify when additional information is needed before making a decision. Adapt communication style when needed to promote effective teamwork. Demonstrate reliability and accountability in completing tasks. Build positive working relationships across campus departments. Stay aware of basic cybersecurity and data privacy practices. Assist in the development and implementation of time series forecasting models Prepare, clean, and manage large datasets for analysis Conduct spatial data processing, including geocoding and integration of geographic units Support the translation and optimization of analytical workflows into Python-based code Collaborate with research staff to evaluate model performance and refine predictive approaches Document processes and contribute to research reports and presentations Current PhD student in Data Science or closely related field Experience with Python for data analysis Familiarity with time series analysis or forecasting methods Basic understanding of geospatial data Strong attention to detail and ability to work with complex datasets Ability to communicate analytical findings clearly Experience with advanced forecasting models (e.g., machine learning or deep learning approaches for time series) Familiarity with working on public safety or social science datasets