Data Scientist

UCSF•San Francisco, CA

3h•$120,000 - $125,000

About The Position

The NeuroAI Lab at UCSF, led by Assistant Professor Pedro Pinheiro-Chagas, is hiring a Data Scientist to support research at the intersection of AI and cognitive neuroscience. The role contributes to a multidisciplinary team developing AI systems for the discovery, diagnosis, and care of neurodegenerative diseases. Research areas include foundation AI models using large-scale clinical databases to identify disease subtypes and risk factors, agentic AI decision-support systems that synthesize multimodal patient data for specialist-level diagnoses, and conversational AI agents for scalable clinical assessments. The Data Scientist designs and maintains data pipelines; curates and analyzes complex multimodal datasets, including clinical notes, neuropsychological assessments, and neuroimaging; develops and evaluates machine-learning models; and contributes to research publications. The position works across the lab’s research areas and offers professional growth in health AI, with exposure to clinical collaborators and the potential to contribute to patient care. The NeuroAI Lab operates at the UCSF Memory and Aging Center, Department of Neurology, and Weill Institute for Neuroscience. It is also affiliated with the Bakar Computational Health Sciences Institute and the Center for Intelligent Imaging.

Requirements

Bachelor’s degree in a related area and/or equivalent experience or training.
Proficiency in Python, with demonstrated experience in data analysis, machine learning, and statistical modeling.
Experience building and maintaining data pipelines, integrating APIs, and working with large-scale datasets.
Familiarity with Git and collaborative software-development practices.
Strong analytical and problem-solving skills, including the ability to work independently and manage multiple projects.
Excellent written and verbal communication skills.

Nice To Haves

Master’s or Ph.D. in Computer Science, Data Science, Biomedical Informatics, Computational Neuroscience, Biostatistics, or a related quantitative field.
Experience with large language models (LLMs).
Familiarity with clinical, cognitive, or health-related datasets, such as electronic health records, neuroimaging, or neuropsychological assessments.
Knowledge of data security, privacy, and regulatory standards for clinical applications, such as HIPAA compliance.
Experience with deep-learning frameworks such as PyTorch or TensorFlow and with cloud-computing platforms.
Track record of peer-reviewed publications or contributions to open-source projects.
Interest in or experience with agentic AI architectures, retrieval-augmented generation (RAG), or multi-agent systems.
Ability to thrive in a fast-paced, multidisciplinary research environment.

Responsibilities

Plan long-term statistical studies, including preparing proposals, designing survey instruments, and determining sampling procedures.
Gather, analyze, prepare, and summarize information and data; recommend statistical approaches, trends, sources, and uses.
Prepare data for presentation.
Identify multivariate strategies.
Prepare study reports for internal validation and cross-validation studies.
Analyze interrelationships among data and define logical aspects of data sets.
Develop systems for organizing data to analyze, identify, and report trends.
Manage research-data databases for projects.
Review new software instruments and their potential effects on statistical testing; make programming modifications as needed.
Participate in developing and implementing data-security policies and procedures.
Keep abreast of technical advances in storage, documentation, and dissemination of computerized data.
Design and maintain robust data pipelines; curate and analyze complex multimodal datasets; develop and evaluate machine-learning models; and contribute to research publications.