Data Scientist

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 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 and enhance 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 are
  integrated into every model developed and deployed.
• Bias
  & Fairness Testing:Conduct rigorous
  statistical bias and fairness evaluation strategies for models developed
  by UCLA Health teams and external vendors, ensuring equitable AI solutions
  that reflect the diversity of our patient population.
• Deliver
  Actionable Insights:Interpret model outputs
  and effectively communicate insights to stakeholders at various technical
  levels. Use strong storytelling, visualization, and communication skills
  to drive alignment and impact across clinical, operational, and executive
  audiences.
• Drive
  Collaboration & Innovation:Foster a culture of
  collaboration across departments by sharing knowledge, best practices, and
  new developments in AI/ML. Operate effectively in agile, cross-functional
  teams and help structure clear, actionable work plans to guide team
  execution.
• Leverage
  Advanced AI/ML Techniques:Utilize large language
  models (LLMs), generative AI, and agentic AI frameworks 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.
  Guide project scoping and execution to ensure relevance, feasibility, and
  impact.

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, with the ability to
  explain complex technical concepts and influence decision-making
• Demonstrated
  experience leading data science projects with structured work plans, clear
  milestones, and timely, high-quality deliverables
• 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, 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 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 May 2025.

Technical Skills

• Master's degree in Computer Science, Mathematics, Statistics, Engineering, or other computational/quantitative field is required. PhD is preferred.
• 2 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 like TensorFlow, Keras, and scikit-learn.
• Demonstrated expertise in leveraging advanced AI techniques, including LLMs and generative AI, to address complex challenges such as predictive analytics and content extraction.
• Experience with Microsoft Azure or similar cloud-based technologies and analytics platforms such as Databricks is preferred.
• Proficiency in Python or R is required, and experience using analytical documentation and development tools, including Jupyter Notebooks, Databricks, or iPython notebooks, to structure and present analyses is preferred.
• Strong programming skills, including shell scripting, Python, Perl, C++, SQL, and Java, are preferred.
• Proficiency in documenting workflows, methodologies, and assumptions to support MLOps practices and ensure transparency, reproducibility, and ethical AI practices.
• Experience with data visualization tools like Tableau, Power BI, matplotlib, or ggplot2 is required.
• 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, with the ability to synthesize and analyze large datasets, identify patterns, and integrate structured and unstructured data for model development.
• Demonstrated experience synthesizing data to produce actionable recommendations and optimize objectives.
• Organizational and Communication Skills
• Excellent written and verbal communication skills, with the ability to explain complex quantitative models to stakeholders at all levels.
• Proven problem-solving skills, including identifying root causes, evaluating solutions, and delivering data-driven outcomes for organizational objectives.
• Exceptional collaboration skills, including active listening, rapport building, consensus building, and effective delegation.
• Experience organizing work, generating task lists, balancing multiple projects, and effectively reporting progress is required.
• Strong organizational and interpersonal skills to thrive in a collaborative and fast-paced environment.

• 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 across the organization.
• Ability to identify, document, and resolve issues effectively while maintaining an organized issues log.
• High-functioning team skills with the ability to balance multiple competing tasks efficiently.