Los Angeles County (CA)
PREDICTIVE DATA ANALYST / EMERGENCY APPOINTMENT HOMELESSNESS Job at Los Angeles
Los Angeles County (CA), Los Angeles, CA, US
EXAM NUMBER:
PH1762B-EA
TYPE OF RECRUITMENT:
OPEN COMPETITIVE - EMERGENCY
FIRST DAY OF FILING:
The application filing period will begin on Thursday, July 17, 2025 at 8:30 a.m. (PT) - Continuous. We will keep accepting applications until the position is filled. The application window may close unexpectedly once we have enough qualified candidates. 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 Predictive Data Analyst 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 Predictive Data Analyst. The Predictive Data Analyst positions are located within the Evaluation Section of the Health Outcomes and Data Analytics (HODA) Division of the Substance Abuse Prevention & Control Bureau. The Predictive Data Analyst will assist with the design, development, and planning implementation of evaluation services and highly complex data science projects which will significantly contribute to the overarching goals of optimizing program effectiveness, ensuring regulatory compliance, and promoting health equity within the managed care framework.DEFINITION:
Under immediate supervision, assists in maintaining and analyzing County, departmental, or divisional data assets; utilizes classical and machine learning techniques, including predictive and prescriptive analytics, to support data-driven program design and management; and produces dashboards, reports, and other advanced data visualization products to help program managers monitor outputs and outcomes.CLASSIFICATION STANDARDS:
This is the first working level in the professional data science/analysis series. Positions allocable to this class work under the immediate supervision of a Data Scientist Supervisor, or supervisor or manager responsible for the data analytics, research, or statistical function of a department, to analyze and maintain the quality of County, departmental, or divisional data assets. Incumbents perform regular quality-assurance analysis upon relevant data sets and work with data administrators and other information technology staff to establish data pipelines and identify issues in need of correction. Incumbents use major statistical programming languages and packages to deploy well-established machine learning and advanced data visualization techniques to complete well-defined, routine-to-moderately-difficult functions and projects. Incumbents may oversee smaller or more routine projects and contribute to larger, more complex projects overseen by a Data Scientist or Senior Data Scientist. Predictive Data Analyst is distinguished from the higher-level Data Scientist in that the latter independently completes moderately complex data science projects or major aspects of large/complex projects, which may include developing new analytic methods, functions, or data architectures, whereas Predictive Data Analysts apply well-established analytic principles, methods, and procedures within existing data systems and architectures to complete well-defined, routine-to-moderately-difficult functions and projects. 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.- Assists with the design, development, and planning implementation of evaluation services and highly complex data science projects by collaborating with the Sr Data Scientist and SAPC program staff, contracted providers, and other stakeholders, that are needed to drive planning, and policy decisions to reduce cost, promote quality of care, and implement value-based SUD treatment and prevention services including but not limited to forecasting utilization and cost, cost/finance analyses, cost-effectiveness analyses, and predictive/prescriptive data modeling to identify investment prioritization, design interventions, and measure outcomes, identifying existing and emerging trends and gaps in care to maximize revenue, and to reduce the cost of unnecessary waste and over/under utilization of services.
- Conducts predictive data assignments for Behavioral Health Quality Improvement Projects (BHQIP) and performance improvement projects (PIPs) mandated by the state and External Quality Review Organization (EQRO) by identifying areas for improvement within SAPC's programs and services through complex data analysis and performance metrics.
- Collaborates with Sr Data Scientist, program managers, patients, stakeholders, and provider network members to develop and implement strategies to address identified areas of improvement and enhance program effectiveness and efficiency.
- Assists with the program performance evaluation, ensuring adherence to regulatory requirements, fidelity, outcomes and effectiveness of various funding programs and grants including CalWORKs and General Relief, Measure H, Behavioral Health Bridge Housing (BHBH), Assembly Bill (AB) 109, Care First and Community Investment, Block Grants, and state or federal grant awards.
- Utilizes advanced statistical techniques and methodologies to analyze large-scale service utilization data (e.g., service utilization by CPT codes, level of care, and provider type, and agency) to predict at-risk and high utilizers and risk performance areas, and initiating other projects.
- Utilizes big data collected via Sage in addition to Census, and Medical Eligibility Data System (MEDS) data to conduct predictive/prescriptive data modeling that will inform SAPC leadership to make better financial, business, policy and operational decisions in managing costs, utilization, and quality of care as well as financial risk management.
MINIMUM REQUIREMENTS:
OPTION I: A Bachelor's degree* from an accredited college or university 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.* AND-
Two (2) years of experience in the application of techniques of machine learning, predictive analytics, data management, and hypothesis-driven data analysis to complex experimental designs leading to actionable findings and recommendations. OPTION II: A Bachelor's degree* from an accredited college or university 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.* AND -
A Master's or Doctoral degree from an accredited college or university in a field of applied research such as Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health. OPTION III: Four (4) years of experience with responsibility for planning, designing, conducting, and evaluating research projects involving the application of techniques of machine learning, predictive analytics, data management, and/or hypothesis-driven data analysis to complex experimental designs leading to actionable findings and recommendations.LICENSE:
A valid California Class C Driver License or the ability to utilize alternative method of transportation when needed to carry out job-related essential functionsPHYSICAL 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.SPECIAL REQUIREMENT INFORMATION:
You MUST meet the above requirement(s) in order to be appointed to fill any vacancies related to this recruitment. * In order to receive credit for any type of college or university course work you must attach a legible copy of the Official Transcript(s) from the accredited institution, which shows the area of specialization and the date the degree was awarded, with Registrar's signature and school seal, with your application online at the time of filing or within seven (7) calendar days from application submission to HRExams@ph.lacounty.gov or your application may be rejected. To receive credit for your Master's or Doctorate degree, you must attach a legible copy of the Official Diploma, Official Transcript(s), or Official Letter from the accredited institution, which shows the area of specialization and the date the degree was awarded, with Registrar's signature and school seal, to the application or within seven (7) calendar days from application submission to hrexams@ph.lacounty.gov. The document should show the date the degree was conferred and be in English; if it is in a foreign language, it must be translated and evaluated for equivalency to U.S. standards. For more information on our standards for educational documents, please visit: and- Accredited institutions are those listed in the publications of regional, national, or international accrediting agencies, which are accepted by the Department of Human Resources (DHR). Publications such as American Universities and Colleges and International Handbook of Universities are acceptable references. Also acceptable, if appropriate, are degrees that have been evaluated and deemed to be equivalent to degrees from United States accredited institutions by an academic credential evaluation agency recognized by The National Association of Credential Evaluation Services (NACES) or the Association of International Credential Evaluators, Inc. (AICE). (see Employment Information under Accreditation Information).
- Official Transcript is defined as a transcript that bears the college seal and states "official and/or copy" issued by the school's registrar office. A printout of the transcript from the school's website is NOT considered official and will not be accepted and may result in your application being incomplete and rejected.
- We do not accept password-protected documents. Ensure documents are unlocked before attaching to your application or sending to the exam analyst.