DATA SCIENTIST / EMERGENCY APPOINTMENT HOMELESSNESS

Los Angeles County (CA)•Los Angeles, CA

64d

About The Position

The LA County Board of Supervisors recently declared a local state of emergency for homelessness, and the County is working to revise and expand our response to help all who are affected. We are looking for qualified and passionate individuals to help us in the mission of addressing issues like housing, mental health, and substance use. If you are looking for a new career that will directly benefit the population of LA County, this may be the opportunity for you. 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. Before the end of your initial work period, you will be assessed on your work performance. This assessment will be weighted 100%. Those who successfully pass the assessment will be considered for permanent appointment to Data Scientist. The Data Scientist positions are located within the Evaluation Section of the Health Outcomes and Data Analytics (HODA) Division of the Substance Abuse Prevention & Control (SAPC) Bureau. The Data Scientist will support data collection and evaluation of services for the CalAIM JI Initiative. The Data Scientist will handle local and state data reports, evaluate program effectiveness (e.g., treatment linkage, timely access, care coordination), and collaborate closely with SAPC's System of Care, IT, Sage Management Divisions, and external stakeholders. DEFINITION: Under general supervision, develops and applies methods to identify, collect, process, organize, and analyze structured and unstructured data using statistical prediction, inference, and optimization; effectively communicates results to County, departmental, and divisional decision makers to support data-driven program design and management. CLASSIFICATION STANDARDS: This is the second working level in the professional data science/analysis series. Positions allocable to this class work under the general direction of a Data Science Supervisor or supervisor or manager responsible for the data analytics, research, or statistical function of a department, independently performing duties of considerable difficulty to complete moderately complex projects or major aspects of large/complex projects that may be divisional, departmental, or Countywide in scope. Incumbents deploy techniques such as data extraction, transformation, and loading; classical statistical analysis and machine learning, including predictive and prescriptive modeling and optimization; and data visualization, to generate critical information and knowledge and effectively communicate findings to technical and nontechnical stakeholders to support data-driven program design, management, and decision-making. Incumbents work with data sets characterized by large volume, moderate complexity, and significant heterogeneity, integrating data from various sources, requiring direct collaboration with data engineers and other IT staff to design and provide feedback on data systems and processes necessary to support their work. Data Scientist is distinguished from the Senior Data Scientist in that the latter applies subject-matter expertise to identify new and emerging business problems, whereas the Data Scientist works under general supervision to develop methods of interrogating data in order to solve previously identified business problems. The Data Scientist is distinguished from the Predictive Data Analyst in that the latter applies well-established analytic principles, methods, and procedures within existing data systems and architectures to complete well-defined, routine to moderately difficult functions and projects, whereas Data Scientists may develop or assist in developing new analytic methods, functions, and data architectures as necessary to complete complex projects, including those involving unstructured data. Positions in this class differ from those that plan, design, conduct and evaluate research projects involving complex experimental designs and data analysis, programming, and processing of data, and preparing reports and recommendations based on research findings, in that these classes do not employ machine learning or big data as part of their analyses.

Requirements

OPTION I: 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.
OPTION II: 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 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 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.
Experience at the level of Predictive Data Analyst is defined as using machine learning techniques to analyze complex data sets and find statistically significant, meaningful predictive patterns, relevant to program goals, that human intelligence could not identify on its own.

Nice To Haves

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.

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. Develop and maintain 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.

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