Senior Data Scientist / Emergency Appointment Homelessness

County of Los Angeles•Los Angeles, CA

2d•Onsite

About The Position

The County of Los Angeles Department of Public Health is seeking qualified candidates to fill emergency Senior 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. 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 Senior Data Scientist. DEFINITION: Under general supervision, leads the development and application of methods to identify, collect, process, organize, and analyze structured and unstructured data using advanced statistical prediction, inference, and optimization; effectively communicates results to County, departmental, and divisional decision makers and provides ongoing support to strengthen data-driven program design and management.

Requirements

Two (2) years of experience carrying out complex data science projects that included independently developing and applying methods to identify, collect, process, structure, and analyze data using statistical prediction, inference, and optimization to support data-driven program design and management, at a level equivalent to the Los Angeles County class of Data Scientist.
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- Six (6) years of experience, including two (2) years in a lead capacity, applying and overseeing the application of machine learning, predictive analytics, data management, and hypothesis-driven data analysis to make actionable recommendations to support 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 as 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 an alternative method of transportation when needed to carry out job-related essential functions.

Nice To Haves

Complex data science projects include artificial intelligence (AI), machine learning (ML), or sophisticated algorithms.

Responsibilities

Collaborates with division, departmental, and countywide stakeholders to solicit, define, and manage highly complex data science projects from conception through implementation; ensures that projects result in actionable insights and recommendations that can be used to support business decisions and allocate resources; and provides ongoing consultation during program implementation of recommendations as necessary to ensure program fidelity.
Provides technical oversight to small teams of Data Scientists and Predictive Data Analysts as necessary to ensure project success.
Leads the discovery process with departmental stakeholders to document business requirements and frame business problems so that appropriate corresponding data science techniques and products can be identified and deployed.
Collaborates with other 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; and provides guidance to other department data experts in the selection and transformation of such sources.
In conjunction with the Information Technology organization, supports collection, integration, and retention requirements for large sets of structured and unstructured data from disparate sources; acts as a resource for senior data engineers and architects in the selection and design of systems for use by the data science team.
Reviews proposals by Data Scientists and analysts regarding selection and improvement of data science tools and ensures that the team’s tools and systems are well documented.
Conducts and coordinates statistical inference of data and conveys findings and conclusions 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 retain fidelity to best practices identified through the analysis and recognize the operational realities underlying existing business processes; provides ongoing consultation as recommended changes and new programs grow and evolve, including recommending modifications to adopted goals and metrics.
Coordinates with various functional teams to develop and implement products, services, tools, or business process changes resulting from the analysis.
Creates and validates advanced analytic products (e.g., Recommender Engines, Auto Classification algorithms, Predictive Scoring, geo-spatial clustering, NLP classifier, etc.) and places them in production; works with nontechnical program managers and staff to understand analytic products and to integrate them into departmental programs.
Recommends ongoing improvements to methods and algorithms that lead to findings, including new information.
Creates and monitors performance of automated-detection systems and provides business metrics for overall project to show improvements 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.
Develops and maintains a high level of expertise in statistical programming languages and packages and other software tools; provides training and support to Data Scientists and Predictive Data Analysts as necessary; and ensures the quality of code and programming logic generated by the data science team.