DATA SCIENTIST / EMERGENCY APPOINTMENT HOMELESSNESS

About the role

The County of Los Angeles Department of Public Health is seeking qualified candidates to fill emergency Data Scientist vacancies related to the homelessness crisis. Under the emergency order, applicants who meet the requirements may be hired for an initial period of up to 90 days, with an opportunity for permanent County employment.

Responsibilities

• Handles data requests from California and Los Angeles County Correctional Facilities regarding individual’s substance use disorder (SUD) treatment history by verifying Releases of Information (ROI) and conducting data mining and analysis across multiple datasets in Sage (e.g., screening/assessments, CalOMS, claims) to respond timely and effectively;
• Maintains transparency through detailed records of all data requests, analyses, and outcomes;
• Develops and implement advanced data science projects to evaluate CalAIM JII’s effectiveness by analyzing key metrics such as treatment linkage, timely access, professional-to-professional warm hand-off, and care coordination outcomes;
• Collaborates with SAPC divisions and stakeholders to provide data insights for strategic decisions, program improvement, and impact maximization;
• Contributes to the design and continuous improvement of data collection methods and performance indicators for pre-release and post-release services, ensuring effective coordination with Correctional Facility Pre and post-release Care Managers;
• Utilizes advanced statistical and machine learning methods to uncover trends, predict outcomes, and inform interventions;
• Develops and maintains dashboards and reports to present findings to stakeholders and program leadership;
• Uses analytical software (e.g., SAS, R, Python), other computer languages (e.g., SQL), data visualization tools (e.g., SAS Visual Analytics, Power BI, Tableau), and advanced data visualization techniques to develop and present data visualizations of findings and recommendations from evaluation and predictive modeling projects to support SAPC’s data-driven policy and operational decisions for SAPC’s CalAIM JII implementation.

Requirements

• Two (2) years of experience applying advanced statistical analyses, including predictive analytics, to produce actionable recommendations to support data-driven program, policy, and operational decision-making, at a level equivalent to the Los Angeles County class of Predictive Data Analyst*
• A Bachelor’s degree** from an accredited college in a field of applied research such as Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health that included 12 semester or 18 quarter units of coursework in data science, predictive analytics, quantitative research methods, or statistical analysis.
• Four (4) years of experience applying machine learning, predictive analytics, data management, and hypothesis-driven data analysis to produce actionable recommendations to support data-driven program, policy, and operational decision-making.
• A Master’s or Doctoral degree*** from an accredited college or university in a field of applied research such Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health may substitute for up to two (2) years of experience.
• A valid California Class C Driver License or the ability to utilize alternative method of transportation when needed to carry out job-related essential functions.

Physical Class

Physical Class II – Light : This class includes administrative and clerical positions requiring light physical effort that may include occasional light lifting to a 10 pound limit and some bending, stooping, or squatting. Considerable ambulation may be involved.