DATA SCIENTIST SUPERVISOR - EMERGENCY APPOINTMENT (HOMELESSNESS)

• Plans, organizes, supervises, manages, and evaluates highly technical and complex assignments of the section; with staff, develops, implements, and monitors data science projects from inception to implementation to ensure that the objectives and desired outcomes are achieved, and that critical decisions are made in a timely manner.

• Plans, assigns, and reviews the work of data scientists and analysts to ensure accuracy, completeness, and compliance with business needs; ensures that section products and services continue to perform as desired over time and directs updates and modifications to these as necessary.

• Collaborates with IT group and program managers to identify departmental or divisional business needs and issues of strategic importance; implements enhancements to existing systems, recommends alternative systems, and assists in developing and implementing new data engineering, data modeling, and data science solutions as appropriate.

• In conjunction with the governance board and executive committees, defines the overall vision and strategy for data analytics across the organization.

• Assists to develop, implement, and evaluate divisional/departmental initiatives, strategies, and operational objectives through deployment of big data; advocates for measurability in strategic planning and operations in order to build analytics and evaluation into program design on a foundational level.

• Evaluates, manages, and participates in all aspects of the section’s solution development, including quality assurance and maintenance of data sets integrated from multiple sources; exploratory data analysis; model creation, testing, and deployment; presentation of findings; and consultation with program managers regarding effective operationalization and model fidelity to improve business outcomes.

• Directs the development of technical reports, dashboards, data briefs, white papers, and publications, including advanced data visualization tools.

• Works with IT data engineers and architects to develop and maintain large-scale databases that meet high standards for completeness, accuracy, and utility; supervises and participates in quality control checks of data extraction, transformation, and loading (ETL) of large-scale, structured, unstructured, and streaming data.

• Advises divisional/departmental managers on opportunities and gaps in their current capabilities across data science technology and infrastructure; recommends plans for growth through adoption of new methods and technologies.

• Builds solutions that apply machine learning techniques to address complex business problems, derive actionable insights, and maximize decision-making confidence.

• Makes recommendations, develops technical infrastructure and analytic competencies, and participates in project selection to inform and execute the data science strategy of the County, department, or division.

• Stays current with and contributes to discovery of data science best practices; mentors staff and ensures the section maintains ongoing training and professional development and is competent in all techniques necessary to complete their duties; and participates in the broader data science community to identify and disseminate the latest developments in data and technology.

• Serves as a technical resource for divisional/departmental managers on data-driven program design and management and the translation of data science and knowledge into improved business outcomes, efficiency, and effectiveness of business processes.

Option I: Two (2) years of experience leading the development and application of methods to identify, collect, process, and analyze data using advanced statistical prediction, inference, and optimization, and providing ongoing support to decision makers to strengthen data-driven program design and management, at a level equivalent to the Los Angeles County class of Senior Data Scientist*.

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, research methods or statistical analysis -AND- Eight (8) years of experience, including four (4) years supervising a team of data science professionals and serving as subject matter expert, and coordinating and overseeing complex data science projects 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 Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health may substitute for up to two (2) years of experience.