Data Scientist
UCLA Health, Los Angeles, CA, United States
Onsite or Remote, Flexible Hybrid
Work Schedule: Monday-Friday, 8:00am – 5:00pm PST
Posted Date: 04/22/2026
Salary Range:
$105,700 – $234,500 annually
Employment Type: Indefinite
Job #29887
Primary Duties and Responsibilities
Transform Healthcare with 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 and LLMOps frameworks, 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 clinical, operational, and financial processes across the UCLA Health system. Lead projects end‑to‑end, from framing the problem to delivering high‑quality outputs on schedule.
Enhance MLOps, LLMOps & Responsible AI Governance: apply and advance our ML and LLM operations paradigms and uphold our AI governance framework, ensuring ethical and scalable AI practices integrated into every model.
Bias & Fairness Testing: conduct rigorous statistical bias and fairness evaluation strategies for models developed by UCLA Health teams and external vendors.
Deliver Actionable Insights: interpret model outputs and effectively communicate insights to stakeholders at various technical levels using storytelling, visualization, and communication skills.
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), generative AI, and agentic AI frameworks.
Identify AI/ML Solutions for Stakeholder Needs: collaborate with clinical, financial, and operational teams to identify opportunities that address key business challenges.
Seeking a candidate with:
Extensive hands‑on experience with large language models (LLMs) and generative AI techniques.
Strong understanding of MLOps, LLMOps, responsible AI governance, and bias/fairness testing methodologies.
Excellent communication and stakeholder engagement skills.
Demonstrated experience leading data science projects with structured work plans.
Deep knowledge of healthcare systems and an understanding of clinical, financial, and operational challenges.
Ability to work in an innovation‑driven, agile environment, continuously learning and applying the latest AI/ML technologies with strong statistical and experimental foundations.
Additional Information
Epic Certification: selected candidates will be required to complete Epic certifications within six 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 May 2026.
This is a flex‑hybrid role requiring presence on‑site at least 20% of the time, and as needed based on operational requirements. Candidates must live in the Greater Los Angeles area or be willing to relocate. 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 $105,700 – $234,500 annually. The University anticipates offering a salary between the minimum and midpoint of this range.
Job Qualifications
Master’s degree in Computer Science, Mathematics, Statistics, Engineering, or related computational/quantitative field is required; PhD is preferred.
Two or more years of experience in advanced analytics, statistical modeling, and code development, including expertise in neural networks, deep learning, NLP, supervised and unsupervised learning, and frameworks such as TensorFlow, Keras, and scikit‑learn.
Demonstrated expertise in leveraging advanced AI techniques, including LLMs and generative AI.
Experience with Microsoft Azure or similar cloud‑based technologies and analytics platforms such as Databricks.
Proficiency in Python or R is required; experience using Jupyter Notebooks, Databricks, or iPython notebooks is preferred.
Strong programming skills including shell scripting, Python, Perl, C++, SQL, and Java.
Proficiency in documenting workflows, methodologies, and assumptions to support MLOps practices.
Experience with data visualization tools such as Tableau, Power BI, matplotlib, or ggplot2.
Experience performing statistical analysis to quantify model limitations and ensure ethical AI practices, including bias and fairness testing.
Experience with healthcare data and/or EHR data is preferred.
Strong metadata management skills.
Demonstrated experience synthesizing data to produce actionable recommendations.
Excellent written and verbal communication skills, with the ability to explain complex quantitative models to stakeholders at all levels.
Proven problem‑solving skills.
Exceptional collaboration skills.
Experience organizing work, generating task lists, balancing multiple projects, and reporting progress.
Strong organizational and interpersonal skills.
Ability to transfer knowledge and concepts to implementation teams and mentor team members.
Strong staff development, leadership, and coaching skills.
Demonstrated ability to influence stakeholders, lead discussions, and present findings to clinical and business leaders.
Ability to identify, document, and resolve issues.
High‑functioning team skills with ability to balance multiple competing tasks efficiently.
As a condition of employment: the final candidate who accepts an 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, or have filed an appeal of a finding of substantiated misconduct with a previous employer.
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Work Schedule: Monday-Friday, 8:00am – 5:00pm PST
Posted Date: 04/22/2026
Salary Range:
$105,700 – $234,500 annually
Employment Type: Indefinite
Job #29887
Primary Duties and Responsibilities
Transform Healthcare with 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 and LLMOps frameworks, 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 clinical, operational, and financial processes across the UCLA Health system. Lead projects end‑to‑end, from framing the problem to delivering high‑quality outputs on schedule.
Enhance MLOps, LLMOps & Responsible AI Governance: apply and advance our ML and LLM operations paradigms and uphold our AI governance framework, ensuring ethical and scalable AI practices integrated into every model.
Bias & Fairness Testing: conduct rigorous statistical bias and fairness evaluation strategies for models developed by UCLA Health teams and external vendors.
Deliver Actionable Insights: interpret model outputs and effectively communicate insights to stakeholders at various technical levels using storytelling, visualization, and communication skills.
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), generative AI, and agentic AI frameworks.
Identify AI/ML Solutions for Stakeholder Needs: collaborate with clinical, financial, and operational teams to identify opportunities that address key business challenges.
Seeking a candidate with:
Extensive hands‑on experience with large language models (LLMs) and generative AI techniques.
Strong understanding of MLOps, LLMOps, responsible AI governance, and bias/fairness testing methodologies.
Excellent communication and stakeholder engagement skills.
Demonstrated experience leading data science projects with structured work plans.
Deep knowledge of healthcare systems and an understanding of clinical, financial, and operational challenges.
Ability to work in an innovation‑driven, agile environment, continuously learning and applying the latest AI/ML technologies with strong statistical and experimental foundations.
Additional Information
Epic Certification: selected candidates will be required to complete Epic certifications within six 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 May 2026.
This is a flex‑hybrid role requiring presence on‑site at least 20% of the time, and as needed based on operational requirements. Candidates must live in the Greater Los Angeles area or be willing to relocate. 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 $105,700 – $234,500 annually. The University anticipates offering a salary between the minimum and midpoint of this range.
Job Qualifications
Master’s degree in Computer Science, Mathematics, Statistics, Engineering, or related computational/quantitative field is required; PhD is preferred.
Two or more years of experience in advanced analytics, statistical modeling, and code development, including expertise in neural networks, deep learning, NLP, supervised and unsupervised learning, and frameworks such as TensorFlow, Keras, and scikit‑learn.
Demonstrated expertise in leveraging advanced AI techniques, including LLMs and generative AI.
Experience with Microsoft Azure or similar cloud‑based technologies and analytics platforms such as Databricks.
Proficiency in Python or R is required; experience using Jupyter Notebooks, Databricks, or iPython notebooks is preferred.
Strong programming skills including shell scripting, Python, Perl, C++, SQL, and Java.
Proficiency in documenting workflows, methodologies, and assumptions to support MLOps practices.
Experience with data visualization tools such as Tableau, Power BI, matplotlib, or ggplot2.
Experience performing statistical analysis to quantify model limitations and ensure ethical AI practices, including bias and fairness testing.
Experience with healthcare data and/or EHR data is preferred.
Strong metadata management skills.
Demonstrated experience synthesizing data to produce actionable recommendations.
Excellent written and verbal communication skills, with the ability to explain complex quantitative models to stakeholders at all levels.
Proven problem‑solving skills.
Exceptional collaboration skills.
Experience organizing work, generating task lists, balancing multiple projects, and reporting progress.
Strong organizational and interpersonal skills.
Ability to transfer knowledge and concepts to implementation teams and mentor team members.
Strong staff development, leadership, and coaching skills.
Demonstrated ability to influence stakeholders, lead discussions, and present findings to clinical and business leaders.
Ability to identify, document, and resolve issues.
High‑functioning team skills with ability to balance multiple competing tasks efficiently.
As a condition of employment: the final candidate who accepts an 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, or have filed an appeal of a finding of substantiated misconduct with a previous employer.
#J-18808-Ljbffr