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About This Role
Type of Recruitment
Open Competitive - Emergency
Filing Dates Applications will be accepted from Thursday, October 15, 2026, at 8:00 a.m. (PT) until Thursday, October 22, 2026, 5:00 p.m. (PT). All applications must be received before 5:00 p.m. (PT) on Thursday, October 22, 2026, to be accepted.
Exam Number HH1763B-EA
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 Department of Homeless Services and Housing (HSH) is seeking qualified candidates to fill emergency Health Program Analyst III 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.
During 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. Essential Job Functions
- Collaborates with division, department, and countywide stakeholders to solicit, define, and manage data science projects from conception through implementation, including identifying and developing statements of business problems; conducting exploratory data analysis and data mining; developing model specification requirements; and conducting advanced statistical analyses.
- Develops and presents visualizations of findings and recommendations that can be used to support business decisions and allocate resources.
- Works with departmental stakeholders to document business requirements and helps frame business problems so that appropriate corresponding data science techniques can be identified and applied.
- Collaborates with department subject matter experts to understand, identify, and select available and relevant sources of data for use cases, including internal, external, structured, and unstructured data sources.
- Works with departmental Information Technology organization to support collection, integration, and retention requirements for large sets of structured and unstructured data from various sources and consults with data engineers and architects on the design and architecture of relevant data systems and processes.
- Collaborates with other Data Scientists, Analysts, and IT staff to select, evaluate, improve, and document tools and systems in order to strengthen divisional and departmental analytic capacity.
- Independently conducts advanced analytical studies for the resolution of business problems and transfigures data into critical information by selecting and deploying appropriate advanced statistical techniques such as machine learning, bivariate and multivariate analyses, predictive/prescriptive analytics, and optimization.
- Uses statistical computer scripting, domain-specific, and programming languages and other software and tools to digest, manipulate, prepare, augment, evaluate, analyze, summarize, and visualize data.
- Plans, designs, and manages experiments, consumer surveys, and other data collection projects to augment existing sources of data as necessary to solve business problems.
- Reviews the work of Predictive Data Analysts and other lower-level analysts assigned to project for quality-control purposes.
- Conveys findings and conclusions of work orally, in writing, visually, in presentations, and by developing interactive tools as appropriate to communicate effectively with a wide range of audiences, including technical and nontechnical staff, stakeholders, and members of the public.
- Works with program staff to understand the implications of analyses and to ensure that findings are actionable and support data-driven program, policy, and operational decision-making.
- Assists in implementing recommended business process changes in ways that both retain fidelity to best practices identified through the analysis and recognize the operational realities underlying existing business processes.
- Works with functional teams to develop and implement products, services, and tools, such as dashboards and reports, emerging from the analysis.
- Contributes to advanced analytic products (e.g., Recommender Engines, Auto Classification algorithms, Predictive Scoring, geo-spatial clustering, NLP classifier, etc.) and helps place them in production.
- Recommends ongoing improvements to methods and algorithms that lead to findings, including new information.
- Provides business metrics for departmental projects to show improvements both initially and over multiple iterations. Provides ongoing tracking and monitoring of performance of decision systems and statistical models and troubleshoots and implements enhancements and fixes to systems as needed.
- Accesses ongoing training and professional development to maintain familiarity with current industry and academic research to apply the latest and most useful statistical learning techniques to help extract pattern and trends from data.
- Develops relationships with local academic data science programs to foster recruitment of data science interns and is responsible for overseeing their work on departmental data science projects.
Requirements
Requirements to Qualify 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 -AND- 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.
You MUST meet the above requirement(s) in order to be appointed to fill any vacancies related to this recruitment.
Special Requirement Information
- 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.
To receive credit for your education, include a copy of your official diploma or letter/certificate -AND- official transcript from an accredited institution within seven (7) calendar days of the end of the filing period. Please submit documentation to [email protected] and indicate your name, the exam name, and the exam number. 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:
https://file.lacounty.gov/SDSInter/dhr/070812_PPG123.pdfandhttps://file.lacounty.gov/SDSInter/dhr/205105_PPG_123_ACE_Resource_Guide.pdf ;
We do not accept password-protected documents. Ensure documents are unlocked before attaching to your application or sending to the exam analyst.
License A valid California Class C Driver License or the ability to utilize an 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.
Desirable Qualifications One (1) year of experience within the last four (4) years in one or more of the following: Working with large, fragmented administrative datasets * + - including individual-level records from social services, healthcare, or government programs. + Selecting and applying statistical or machine learning models appropriate to the business problem, including model assumptions and limitations. + Producing recurring reports or dashboards from administrative data systems using tools such as Tableau, Looker, Power BI, Databricks Dashboards, Sparks, Azure Synapse, or equivalent platforms. + Developing dashboards or automated reports that translate analytic outputs into actionable information for program managers or operational staff. + Collaborating with data engineers or IT staff to scope data needs, provide feedback on data systems, and integrate analytic workflows into data pipelines. + Applying version control (e.g., Git) and basic software development practices, such as code documentation and reproducibility standards. + Working on an Extract, Transform, and Load (ETL) process using data input tools to clean and combine datasets.
- Experience presenting data analysis findings to non-technical stakeholders including homeless service program staff, leadership, and external bodies.
Additional Information
Exam Content During your initial work period, the appointing department will evaluate your performance. Those who achieve a passing score on this evaluation will be considered for permanent appointment.
Application and Filing Information
Applications must be filed online only and will be reviewed for interview consideration on an ongoing basis. If you have not been contacted within 60 days and the recruitment remains open or reopens for filing, we encourage you to submit a new application. This will allow you to reaffirm your interest and update any relevant information. Please note, applicants will not receive individual notifications regarding their application or whether they meet the requirements.
Many important notifications will be sent electronically to the email address provided on the application, so it is important that you provide a valid email address. Please add [email protected], as well as [email protected], and [email protected] to your email address and list of approved senders to prevent email notifications from being filtered as spam/junk/clutter mail.
You have the ability to opt out of emails from LA County. If you unsubscribe, you will not receive any email notification for any examination for which you apply with Los Angeles County. Regardless of whether you choose to unsubscribe, you can always check for notifications by logging into governmentjobs.com and viewing your profile inbox, which saves a copy of all emailed notices.
Plan to submit your online application well in advance of the deadline as you may be required to verify your email address. This only needs to be done once per email address, and if you already have a job seeker account on www.governmentjobs.com/careers/lacounty, you can verify at any time by logging in and following the prompts. This is to enhance the security of your online application and to ensure you do not enter an incorrect email address.
Social Security Number
Please include your Social Security Number for record control purposes. Federal law requires that all employed persons have a Social Security Number.
Computer and Internet Access at Public Libraries For candidates who may not have regular access to a computer or the internet, applications can be completed on computers at public libraries throughout Los Angeles County.
Anti-Racism, Diversity, and Inclusion (ARDI) The County of Los Angeles recognizes and affirms that all people are created equal and are entitled to all rights afforded by the Constitution of the United States. The Department of Human Resources is committed to promoting Anti-racism, Diversity, and Inclusion efforts to address the inequalities and disparities amongst race. We support the ARDI Strategic Plan and its goals by improving equality, diversity, and inclusion in recruitment, selection, and employment practices.
Department Contact Name:Suzy Atajayan Department Contact Email: [email protected] Teletype Phone: (800) 735-2929 COUNTY OF LOS ANGELES
Employment Information
Any language contained in the job posting supersedes any language contained below.
This document is intended to provide general information about the recruitment process of the County of Los Angeles. Applicants with questions about a specific job posting should contact the exam analyst listed on the posting.
Equal Employment Opportunity/Non-Discrimination Statement:
The County of Los Angeles is an Equal Employment Opportunity Employer and is committed to non-discrimination in the County workforce, regardless of age (40 and over); ancestry; color; ethnicity; religious creed; protected family or medical leave status; disability; marital status; medical condition; genetic information; military and veteran status; national origin; race ; sex; gender; sexual orientation; or any other characteristic protected by State or federal law. For more information, please visit: https://employee.hr.lacounty.gov/eeo-programs/.
Testing Accommodations for Applicants:
The County of Los Angeles complies with all federal and state disability laws and makes reasonable accommodations for qualified applicants and employees with disabilities. If a reasonable accommodation is needed to participate in the job application process, please contact the testing accommodation coordinator listed on the job posting. Hearing impaired applicants with telephone teletype equipment may leave messages by calling the teletype phone number on the job posting. For more information on accommodations, please visit: https://hr.lacounty.gov/accessibility/.
Fair Chance:
The County of Los Angeles is a Fair Chance employer. Except as otherwise permissible under applicable laws, you will not be asked to provide information about conviction history unless you receive a conditional offer of employment. The County will make an individualized assessment of whether your conviction history has a direct and adverse relationship with the specific duties of the job, and will also consider potential mitigating factors, which may include, but is not limited to, evidence and extent of rehabilitation, recency of the offense(s), and age at the time of the offense(s). If asked to provide information about conviction history, any convictions or court records which are exempted by a valid court order do not have to be disclosed. Qualified applicants with arrest or conviction records will be considered for employment in accordance with County Fair Chance Policies and the Fair Chance Act (Gov. Code Section 12952).
Employment Eligibility:
Final appointment is contingent upon verification of U.S. citizenship or the right to work in the United States.
Career PathFinder:
Resources to help current and prospective employees plan a career with Los Angeles County are available. To explore career paths to and from nearly all job titles, please visit our interactive Career PathFinder application at http://career-pathfinder.hr.lacounty.gov.
Veteran’s Credit:
Pursuant to the County Charter and County policy, in all open competitive examinations (i.e., examinations open to everyone), the County of Los Angeles will add a credit of 10 percent of the total credits specified for such examination to the final passing score of an honorably discharged veteran, as well as the spouse of a deceased or disabled veteran, who served in the Armed Forces of the United States under specific conditions.
For more information on veteran’s credit, please visit: https://file.lacounty.gov/SDSInter/dhr/205102_PPG_115.pdf
Revised September 2025
Salary Context
This $115K-$155K range is below the median for Data Scientist roles in our dataset (median: $162K across 195 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 11,520 AI roles we're tracking, Data Scientist positions make up 4% of the market. At County of Los Angeles, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $190,000 based on 1,564 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($135K) sits 29% below the category median. Disclosed range: $115K to $155K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
County of Los Angeles AI Hiring
County of Los Angeles has 1 open AI role right now. They're hiring across Data Scientist. Based in CA, US. Compensation range: $155K - $155K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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