What are the responsibilities and job description for the AI, Data Science & Advanced Analytics Consultant position at JRD Systems?
Public Works is establishing a comprehensive Data Science Program to enhance data-driven decision-making, improve operational efficiency, and fully leverage modern data platforms such as Databricks in support of the Los Angeles County InfoHub. This initiative is critical to enabling scalable analytics, strengthening data governance, and delivering actionable insights across departmental operations. To effectively implement and mature this program—and to address the increasing demand for predictive analytics and AI-driven solutions—the department requires a highly qualified AI, Data Science & Advanced Analytics Consultant. This resource will provide specialized expertise to accelerate program development, support the design and deployment of advanced analytics solutions, and ensure alignment between data, technology, and business objectives. The consultant will play a key role in establishing foundational capabilities, enabling knowledge transfer to internal staff, and positioning Public Works to sustainably expand its data science and AI initiatives. The AI, Data Science & Advanced Analytics Consultant should possess the following skills and competencies: • Exceptional communication and stakeholder engagement skills, with the ability to clearly translate complex data, analytical models, and AI concepts into actionable insights for both technical and non-technical audiences, while maintaining a strong customer service orientation. • Advanced analytical and business acumen, including experience with statistical methods and modeling techniques such as regression analysis, association analysis, clustering, and outlier detection, along with a solid foundation in exploratory data analysis and problem framing. • Working knowledge of data architecture and database design principles, with the ability to collaborate effectively with Data Management and Data Engineering teams to ensure data quality, accessibility, and alignment with enterprise standards. • Proficiency in data visualization and reporting tools to effectively communicate insights, trends, and performance metrics to support decision-making. • Strong project and time management capabilities, with a proven ability to manage multiple priorities, meet deadlines, and deliver high-quality outputs in a fast-paced, evolving environment. • Demonstrated ability to work both collaboratively and independently, driving initiatives forward with minimal oversight while aligning data, analytics, and business objectives across cross-functional teams. • High attention to detail and commitment to data quality, ensuring accuracy, consistency, and reliability in all analyses, models, and deliverables. • Experience supporting the development and operationalization of data science solutions, including contributing to scalable analytics frameworks and enabling knowledge transfer to internal teams.
Experience Required:
• Five (5) years of experience in data analysis, analytics, data visualization and reporting with the ability to present insights to business and executive stakeholders. • Five (5) years of experience with SQL programming, using data sources such as SQL Server, Oracle, PostgreSQL, or similar relational databases. • Two (2) years of experience working with Databricks, Genie and similar AI cloud-based analytics platforms, including notebook development, feature engineering, Machine Learning model training, and workflow orchestration. • Two (2) years of experience collaborating with data engineering and data science teams to design data pipelines, optimize data transformations, and implement Lakehouse or data warehouse architectures (e.g., Databricks, Snowflake, SQL-based platforms). • One (1) years of experience applying advanced analytics and predictive modeling (e.g., regression, classification, clustering, forecasting, natural language processing).
Education:
This classification requires possession of a Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Information Technology, or a closely related quantitative field. Additional qualifying professional experience may be substituted for the required education on a year-for-year basis. • Industry-recognized certifications in data science or cloud analytics, such as: • Microsoft Azure Data Scientist Associate (DP-100) • Databricks Certified Data Scientist or Machine Learning Professional • AWS Machine Learning Specialty • Google Professional Data Engineer or equivalent advanced analytics certifications.
Additional Information
• California Resident Candidates Only. Work is expected to be HYBRID, and interviews will be conducted on-site. Work schedule will be 4/40, 10-hour day within the M-TH work schedule at the discretion of the program manager. Work shift ranges from 7:15am to 6:00pm.