Data Scientist

Data Scientist I - District Office PRIMARY FUNCTION

The Data Scientist I supports the College's Institutional Research and Data Science function by preparing data, conducting defined components of advanced quantitative analyses, and contributing to statistical, predictive, forecasting, segmentation, and scenario-modeling work. The position applies established analytical methods and Responsible AI procedures under guidance to support institutional research, student success, planning, continuous improvement, and informed decision making. The position assists with evaluating model performance, interpretability, stability, potential bias and fairness risk, privacy implications, limitations, appropriate use, and required human review;

documents findings; and escalates complex methodological, ethical, or use concerns. This work helps the College better understand patterns, trends, risk factors, outcomes, and opportunities for improvement through rigorous, transparent, and responsible use of institutional data.

• Prepare, clean, transform, and structure institutional, operational, academic, student success, workforce, and other relevant datasets for analytical and modeling use.
• Conduct quantitative analyses and exploratory data analysis to identify patterns, trends, relationships, and potential explanatory factors that support institutional decision making.
• Support the development, testing, refinement, and maintenance of statistical, predictive, forecasting, classification, clustering, segmentation, simulation, or other analytical models using approved methods, documented intended uses, and established Responsible AI and human-review procedures.
• Validate analytical outputs, test assumptions, review results for accuracy, and assist with evaluating model performance, calibration, stability, interpretability, potential bias and fairness risk, privacy implications, limitations, fitness for use, and required human review; document concerns and escalate complex issues appropriately.
• Create and maintain reproducible code, variable definitions, methodological records, evaluation results, intended-use and limitation statements, model‑card components, monitoring information, and escalation records for assigned analytical tasks and recurring models, using established standards and seeking guidance on more complex methodological or Responsible AI issues.
• Assist with scenario analyses, projections, sensitivity testing, and other applied analytical work that supports planning, evaluation, institutional effectiveness, and continuous improvement.
• Translate analytical findings into clear summaries, visuals, and presentations for technical and nontechnical audiences, including appropriate explanation of assumptions, uncertainty, limitations, potential bias or fairness concerns, human‑review requirements, appropriate use, and practical implications.
• Collaborate with Data Analysts, Data Pipeline Engineers, AI Application Developers, subject‑matter experts, governance partners, and business stakeholders to understand institutional questions, frame analyses, interpret results, support responsible use of advanced analytics, document evaluation concerns, and route data, model, application, privacy, or governance issues to the responsible role.

• Participate in professional development related to applied statistics, machine learning, forecasting, model validation, responsible analytics, institutional research, and emerging tools relevant to applied data science.
• Serve on councils, committees, task forces, or other work groups as requested to provide institutional research expertise and support for college‑wide projects or initiatives. Other duties as assigned.

• Knowledgeable of and committed to the philosophy of a comprehensive community college, the College's values and institutional goals, and student success.
• Knowledge of data security practices and policies, including FERPA, necessary to protect sensitive or confidential information from intentional or unintentional disclosure.
• Knowledge of applied statistical methods, predictive analytics, forecasting,…