Oakwood, Georgia
Nashville, Tennessee
Nashville, Tennessee
Seattle, Washington
Portland, Oregon
New York, New York
New York, New York
Posted: 19-Sep-24
Location: Los Angeles, California
Salary: Open
Categories:
Internal Number: 142538533
The Advanced Analytics Manager reports directly to the Director of Data Science and plays a key role in executing the strategic vision to advance UCLA Health Information Technology's AI capabilities. This role provides technical leadership and mentorship to a team of highly skilled data scientists, who hold advanced degrees (e.g., PhD, MSc) and possess expertise in advanced computational methods and data science programming languages.
As part of the centralized Advanced Analytics team within the Office of Health Informatics and Analytics, the manager collaborates extensively with UCLA Health and Health Sciences stakeholders, along with other UCLA Health IT teams, to drive clinical, financial, operational, and research initiatives forward.
In this capacity, the manager supports the development and standardization of processes to ensure scalability and repeatability, aligning closely with the organization's AI strategy led by the Director. This strategy emphasizes accelerating AI adoption, increasing AI literacy, building stakeholder trust, and leveraging infrastructure investments to enhance patient care and operational efficiency. A critical aspect of this strategy involves the development and deployment of AI models, including the innovative use of generative AI to solve complex challenges. The manager also plays a pivotal role in supporting AI governance across the organization.
Additionally, the manager is responsible for overseeing work assignments, resource tracking, and team balancing, while collaborating with project and product management teams to ensure tasks are clearly understood, properly estimated, and executed. The manager ensures that all AI initiatives comply with established guidelines and principles, fostering the responsible integration and growth of AI technologies within UCLA Health.
This flexible hybrid role allows for a blend of remote and on-site work, requiring presence on-site as needed based on operational requirements. Please note, travel to the "home office" location is not reimbursed. Each employee will complete a FlexWork Agreement with their manager to outline expectations and ensure mutual understanding. These arrangements are periodically reviewed and may be adjusted or terminated as necessary.
Salary offers are based on a variety of factors including qualifications, experience, and internal equity. The full salary range for this position is $112,900 - $256,900 annually. The University anticipates offering a salary between the minimum and midpoint of this range.
• Master’s degree is required. PhD degree is preferred.
• 2+ years of experience supporting healthcare stakeholders and solutions for clinical, financial, operational, and research or other relevant areas is required
• 5+ years (3+ years with a PhD) of advanced data analysis experience and expertise in diverse statistical, data mining techniques and technologies is required
• 5+ years of proficiency with a statistical language: R or Python is required
• 2+ years of experience working with EHR systems and health-related data is required
• 2+ years of experience working with Microsoft Azure, Databricks, or AWS cloud-based technologies is required
• Experience working with large language models and open-source tools is required
• 2+ years of supervisory or leading teams experience in data science, analytics or any Information Technology areas preferred
• 2+ years of experience with MS SQL Server and/or Oracle
• 2+ years of experience working with Tableau, Power BI or similar data visualization tools
• Demonstrated experience synthesizing and analyzing large data and making program recommendations based on that data is required
• Excellent written and communication skills explaining complex quantitative models to business stakeholders, management and executives
• Ability to take the inferences from data and produce decisions from it that will optimize objectives
• Ability to transfer knowledge and concepts to the team that is implementing the actual system
• Strong problem-solving and metadata skills
