"Biomedical Informatics Data Scientist/Research Data Analyst"

Situated in Stanford’s highly dynamic research environment, the Stanford PEDSnet team and Division of Clinical Informatics seek a Biomedical Informatics Data Scientist/Research Data Analyst to manage and analyze clinical data (i.e. electronic health records, administrative claims data, etc.) under the direction of both the PEDSnet leadership team and Clinical Informatics research team. The Bioinformatician/Research Data Analyst will partner with researchers and clinicians to enable effective and efficient use of the PEDSnet Common Data Model, PCORnet Common Data Model, Epic Cosmos and/or OMOP/OHDSI databases along with their respective cohort query tools and interfaces. This individual will help researchers and clinical staff maximize their understanding, interpretation and use of these clinical and research tools for more informed and productive research, clinical trials, patient care and quality outcome projects.

The job duties listed below are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility.

• Work closely with researchers to implement electronic health record (EHR) studies. This includes building codesets to identify cohorts of patients, developing processes to measure and ensure quality, completeness and integrity of research datasets, and performing iterative analyses to incorporate collaborator feedback.
• Employ new and existing tools to interpret, analyze, and visualize relationships in data. Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data (e.g. selecting and applying the super learner library including parametric and nonparametric candidate algorithms; interpret the results of a model including covariate adjustment).
• Incorporate causal inference considerations to retrospective cohort data.
• Select, apply, tune, and optimize machine learning analysis algorithms.
• Use system reports and analyses to identify potentially problematic data, determine root cause for data problems, and suggest possible solutions for local and/or network-wide changes.
• Develop reports, charts, graphs, and tables for use by investigators and for publication and presentation.
• Manage code changes in shared repositories and follow best practices to support collaborative development workflows.
• Work closely with the engineering team to support the implementation of ETL (extract, transform, load) specifications and quarterly refreshes to the latest common data model (CDM) version.
• Execute site-level queries as part of PEDSnet or PCORnet network and participate in data working groups to discuss data model updates and changes.
• Collaborate with a diverse portfolio of faculty and research groups across the Stanford campus on data collection and analysis methods.
• Represent team on national research projects and grants through presentation of papers, participation in phone calls, working groups and other venues. Assist with grant proposals.
• Provide training to team members and users as appropriate.
• Other duties may also be assigned.

The ideal candidate for this position is an individual with deep knowledge of clinical data, sense of curiosity, quality analysis and validation methodologies; and strong interpersonal skills needed to work collaboratively with technical and non-technical stakeholders within and outside the Stanford research community, including faculty, researchers, clinicians, hospital administrators, engineering teams, IT staff and research coordinators. The Bioinformatician/Research Data Analyst will work closely with Research Technology, other key Stanford School of Medicine teams (Quantitative Sciences Unit, Research Informatics Center), and Stanford Children’s Health teams to develop high quality coherent research-ready biomedical datasets. This individual will be responsible for continuous evaluation of the health of these datasets and enterprise tools used by the research community and for developing new analytical methods supporting novel research.

DESIRED QUALIFICATIONS:

• MS or PhD in Bioinformatics, Data Science, Biostatistics, Epidemiology, or a related field
• 2+ years of experience performing database management and data analysis in research analyses and visualization work in a healthcare research or clinical setting, or other related experience.
• Fluency in SQL, Python and R.
• Self-motivated with a demonstrated ability to work independently, and to exercise independent judgment in developing solutions to complex problems.
• Good interpersonal and communication skills to interact with technical and non-technical stakeholders.
• Ability to receive and incorporate feedback.
• Experience working in academic and/or research environments.
• Experience with Electronic Health Records e.g., Clarity Data Model, Caboodle Data Model
• Experience with common data models like OMOP, PEDSnet, PCORnet or Epic Cosmos
• Experience with ontologies, terminologies, UMLS, or Semantic Web
• Ability to mine and analyze complex structured and unstructured data sets
• Demonstrated knowledge of and experience applying AI/ML techniques (e.g., large language models, natural language processing, predictive modeling) to clinical, EHR, or other biomedical data sources
• Experience using large language model-based coding assistants (e.g., OpenAI Codex) to develop and optimize analysis pipelines
• Experience with semiparametric estimation, and causal inference research methods
• Familiarity with regulatory requirements such as Institutional Review Board (IRB), and HIPAA. Knowledge of regulatory and data privacy issues.

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor's degree and three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

• Substantial experience with MS Office and analytical programs.
• Excellent writing and analytical skills.
• Ability to prioritize workload.

CERTIFICATIONS & LICENSES:

None

PHYSICAL REQUIREMENTS:

• Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
• Occasionally use a telephone.
• Rarely writing by hand.

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS:

Some work may be performed in a laboratory or field setting.

Resources:

1. PEDSnet: https://pedsnet.org/
2. Stanford PEDSnet: https://med.stanford.edu/mchri/crso/pedsnet.html
3. Division of Clinical Informatics: https://med.stanford.edu/peds-clinical-informatics.html
4. Research IT Website: https://med.stanford.edu/sdsr/research-technology.html
5. STARR: https://starr.stanford.edu/
6. Epic Cosmos: https://cosmos.epic.com/