Los Angeles County (CA)-posted about 2 months ago
Full-time • Entry Level
Los Angeles, CA
101-250 employees
Administration of Housing Programs, Urban Planning, and Community Development

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.

  • 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.
  • 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 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.
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