Research Consultant Data Scientist

Role overview This is a client-facing data science position focused on healthcare analytics and real-world evidence generation. The role partners with external collaborators to design studies, curate multimodal clinical datasets, and deliver analytic and AI-ready outputs. The work spans descriptive analytics, predictive and causal modeling, and rigorous documentation for both technical and clinical audiences.

Responsibilities - Collaborate with clients to scope analytic solutions and craft project proposals that address concrete healthcare challenges - Design statistical analysis plans covering methodology, expected outputs, and dataset requirements for evidence-generation projects - Query complex health data sources (EMRs, ECG, DICOM, claims) to identify, map, and curate high-quality datasets for AI and analytic use cases - Build descriptive analyses alongside predictive and causal inference models to generate evidence and improve existing data products - Produce clear written deliverables, including internal documentation, conference submissions, and peer-reviewed publications - Develop HIPAA-compliant SQL and Python (or R) code, manage data quality, and present findings to senior leadership and external stakeholders

Requirements - M.S. or PhD in Biomedical Informatics, Data Science, Biostatistics, or a related field; or a B.S. with at least seven years of relevant experience - Background in statistical modeling and real-world data analysis, with proven client-facing and project leadership experience - Fluency in Python and SQL - 1+ years working with healthcare delivery data such as EMRs, claims, or registries, plus familiarity with content standards (FHIR, CDA, CQL) and clinical terminologies (ICD, CPT, LOINC, SNOMED-CT, NDC, RxNorm) - Strong technical writing, editing, and communication skills, with a collaborative, client-first mindset - Solid organizational skills, comfort managing multiple projects, and ability to plan work against shifting deadlines

Nice to have - Prior experience at or with early-stage startups - Familiarity with Git, encryption methods, regular expressions, and AWS tooling - Hands-on experience with Epic, Cerner, or Allscripts systems - Working knowledge of the OMOP common data model, DICOM imaging, NLP techniques, or general machine learning concepts

Benefits and work setup - Fully remote with flexible hours, with a light meeting load by design - Comprehensive wellness benefits including health, dental, vision, PTO, and sick leave - Dedicated professional development days to build skills - Occasional in-person company working days roughly once per quarter - Mission-driven culture that blends academic rigor with startup pace, emphasizing deep focus time and easy collaborative access to teammates