Data Scientist Supervisor - Los Angeles County, CA, United States - Los Angeles County Department of Human Resources

Mark Lane

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Mark Lane

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Description

EXAM NUMBER:


  • PH1765A

THIS ANNOUNCEMENT IS A REPOSTING TO REOPEN THE FILING PERIOD AND UPDATE BULLETIN INFORMATION.

FIRST DAY OF FILING**:

Wednesday, April 17, 2024 at 8:30 a.m., Pacific Time (PT)-
TYPE OF RECRUITMENT:Open Competitive Job Opportunity
Position Information:


  • Provides administrative and technical supervision to the section responsible for conducting data science projects and other advanced research and analytics for a County department or division; works with senior IT management to build and maintain data infrastructure necessary to support data science; serves as technical resource for departmental managers on the uses of data science to strengthen programs and policy initiatives; and defines overall data analytics vision and strategy.

Classification Standards:


  • This is the highest level in the Data Science series. Positions allocable to this class report to a higherlevel manager responsible for the data analytics, research, or statistical function of a department, and oversee the section responsible for meeting the data science needs of a division or department. Positions supervise staff in the development of sophisticated statistical models and forecasting tools; create, maintain, and leverage big data assets to drive evidencebased program design and management; and construct data science products, such as automated reports and predictive scores, to meet departmental or divisional requirements. Incumbents collaborate with Information Technology staff to scope, design, and build, and administer, maintain, and update largescale databases and data pipelines to support the work of the section. Positions require expert knowledge of and experience in advanced data and statistical modeling and computational methods, statistical programming languages and packages, and bigdata engineering solutions; and the ability to identify and resolve business needs and issues of strategic importance within the assigned department.


Positions in this class differ from those that supervise the planning, design, conduct and evaluation of 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 such projects do not employ machine learning or big data as part of analyses.


Essential Job Functions:


  • 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.

Stays current with and contributes to discovery of data science best

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