Are you passionate about transforming healthcare through cutting-edge AI and ML technologies? We are seeking a highly skilled Data Scientist to drive innovative initiatives and improve healthcare outcomes. This role offers an exciting opportunity to apply your expertise in AI/ML, enhance our MLOps framework, and contribute to the responsible use of AI across our health system.
Key Responsibilities:
Lead AI/ML Initiatives: Develop, evaluate, and validate AI/ML models that support and enhance clinical, operational, and financial processes across the UCLA Health system.
Enhance MLOps & Responsible AI Governance: Apply and advance our ML operations (MLOps) paradigm and uphold our AI governance framework, ensuring ethical AI practices are integrated into every model developed.
Bias & Fairness Testing: Conduct rigorous bias and fairness testing for models developed by UCLA Health teams and external vendors, ensuring equitable AI solutions.
Deliver Actionable Insights: Interpret model outputs and effectively communicate insights to stakeholders at various technical levels, providing data-driven recommendations tailored to their needs.
Drive Collaboration & Innovation: Foster a culture of collaboration across departments by sharing knowledge, best practices, and new developments in AI/ML.
Leverage Advanced AI/ML Techniques: Utilize large language models (LLMs) and generative AI to solve complex healthcare challenges in an ever-evolving technological landscape.
Identify AI/ML Solutions for Stakeholder Needs: Collaborate with clinical, financial, and operational teams to identify AI/ML opportunities that address key business challenges and improve outcomes.
Seeking a candidate with:
Extensive hands-on experience with large language models (LLMs) and generative AI techniques. Strong understanding of MLOps, responsible AI governance, and bias/fairness testing methodologies. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Deep knowledge of healthcare systems and an understanding of clinical, financial, and operational challenges in the healthcare industry. Ability to work in an innovation-driven environment, continuously learning and applying the latest AI/ML technologies.Additional Information:
Epic Certification: Selected candidates will be required to complete Epic certifications within 6 months of hire if not currently certified. Application Instructions: Please upload your cover letter along with your resume into a single PDF file. Selection Timeline: We will be reviewing applications throughout January 2025.If you are excited about applying AI to transform healthcare and thrive in a fast-paced, innovative environment, we encourage you to apply today!
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 $102,500 – $227,700 annually. The University anticipates offering a salary between the minimum and midpoint of this range.
As a condition of employment, the final candidate who accepts a conditional offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; received notice of any allegations or are currently the subject of any administrative or disciplinary proceedings involving misconduct; have left a position after receiving notice of allegations or while under investigation in an administrative or disciplinary proceeding involving misconduct; or have filed an appeal of a finding of misconduct with a previous employer.