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Dandelion Health

Provides de-identified clinical data for AI

Research Consultant Data Scientist

Data ScienceConfirmed live in the last 24 hours
Full-timeRemote in USA$155k - $170k /yr

About the Job

Requirements

  • An M.S. or PhD in a relevant field, such as Biomedical Informatics, Data Science, or Biostatistics, or a B.S. with at least seven years of experience.
  • Experience in client interaction, crafting project proposals, and leading teams.
  • Background in statistical modeling and real-world data analysis.
  • Fluency in Python and SQL.
  • At least one year of experience extracting, curating, and analyzing data created within the health information technology and healthcare delivery ecosystem, such as electronic medical record, claims, or registry data; this may include knowledge of data exchange and content standards such as FHIR, CDA, and CQL, and clinical terminology standards such as ICD, CPT, LOINC, SNOMED-CT, NDC, and RxNorm.
  • Strong technical writing, editing, and communication skills, along with a collaborative, client-first mindset.
  • Organizational skills and the ability to embrace change, manage multiple projects, and plan work to meet deadlines.
  • SQL.
  • Python and/or R.
  • Git and version control.
  • Familiarity with encryption methods and writing regular expressions.
  • Experience querying enterprise data warehouses or databases and creating reports or analytics for healthcare data.
  • Familiarity with the data aspects of electronic medical records, such as Epic, Cerner, and Allscripts.
  • Experience working with insurance claims data.
  • Familiarity with medical terminologies or controlled vocabularies such as ICD-10, SNOMED-CT, LOINC, CPT/HCPCS, NDC, and RxNorm.
  • Medical ontology experience.
  • Natural language processing experience.
  • Experience working with DICOM or other imaging modalities.
  • Experience with the OMOP common data model.
  • Familiarity with machine learning concepts.
  • Experience with AWS.

Responsibilities

  • Collaborate with clients to develop analytic solutions that create value and address business challenges.
  • Design statistical analysis plans for evidence-generation projects, including methodology, results structure, expected outputs, and dataset requirements.
  • Query complex source systems across health data sources, such as electronic medical records, ECG data, and DICOM data, to identify and map data elements and create high-quality datasets for analytic and AI use cases.
  • Develop descriptive analyses and predictive and causal inference models to drive evidence generation on company data and enhance existing data products.
  • Summarize project methods and results in clear explanations and documentation for internal and external audiences, including conference and peer-reviewed publication submissions.
  • Support SQL and analytical programming, data management, quality control, and reporting throughout analytics projects.
  • Develop code and documentation to deliver high-quality, HIPAA-compliant data products on time to internal and external customers.
  • Create summarized findings and recommendations tailored to audiences with varying levels of technical and clinical experience.
  • Identify and resolve problems using relevant knowledge and troubleshooting skills.
  • Ensure accuracy, data integrity, and validity in all data and analysis work.
  • Present to senior leadership and external audiences.
  • Partner with clients to develop data science solutions and analyze AI-ready multimodal datasets.
  • Curate datasets by identifying patient subpopulations or disease cohorts and pooling multimodal data for exploratory AI/ML and real-world evidence analyses, model experimentation, and model validation.
  • Lead analytics research from inception to closeout, owning study design, data curation strategies, effort estimation, analytic design, and delivery of final results.
  • Design and deliver data-driven solutions that help clients address business challenges.

Desired Qualifications

  • Experience working in or with startups is a plus.
  • Familiarity with high-level machine learning concepts is a plus; machine learning model development and deployment experience is not required.

About the Company

Dandelion Health

Provides de-identified clinical data for AI

Dandelion Health provides secure, de-identified clinical data from health systems to support healthcare AI and precision medicine. It aggregates data across multiple clinical modalities from routine practice, offering a centralized, cleaned dataset for researchers, providers, and algorithm developers. Its products work by partnering with health systems to curate and standardize large, diverse datasets, enabling faster data curation (months to days) and powering predictive and prognostic models, biomarker discovery, and clinical trial optimization. A key differentiator is the combination of exceptionally deep, high-quality data with efficient data curation and an emphasis on ethical access, plus an active algorithm validation service (ECG and Chest CT) funded publicly. The company’s goal is to accelerate the development of personalized medicine by making high-quality data and validation resources readily available to support algorithm development and clinical research.

Company size
51-200
Company stage
Series A
Total funding
$29.9M
Headquarters
Oyster Bay, NY
Founded
2020

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