Healthcare Data scientist - Remote
Remote / Online - Candidates ideally in
Richmond, Henrico County, Virginia, 23219, USA
Listed on 2026-07-26
Richmond, Henrico County, Virginia, 23219, USA
Listing for:
Staffing
Remote/Work from Home
position Listed on 2026-07-26
Job specializations:
-
IT/Tech
Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Healthcare Data Scientist
Location:
Remote
Job type:
Contract
US Citizen, Green Card, TN, GC EAD and H4 EAD only. No third-party agencies.
Must-Have Qualities:
- Masters Degree in Computer Science:
The ideal candidate should hold a Masters degree in Computer Science, showcasing a strong academic foundation in relevant fields. - 4 Years of
Experience:
We require at least 4 years of practical experience in data science, encompassing a strong track record of successful projects and contributions. - ETL Pipeline
Experience:
The candidate should have a proven ability to design, build, and optimize ETL (Extract, Transform, Load) pipelines for efficient data processing and analysis. - Python Proficiency:
Profound expertise in Python is a crucial requirement, as the role heavily relies on Python for data analysis, modeling, and visualization.
Nice-to-Have Qualities:
- Experience Deploying Client Models at Scale:
Practical experience in deploying machine learning models at scale would be a significant asset, showcasing the ability to operationalize data science solutions effectively. - Experience Evaluating LLM (Large Language Models):
Familiarity with the evaluation of Large Language Models (LLM) and their applications in data science. - Experience Building Healthcare Client Models:
Experience in developing healthcare-focused machine learning models would be a strong plus.
Soft Skills:
- Analytical Mindset:
We value individuals who can think critically, analyze data effectively, and draw actionable insights from complex datasets. - Effective Communication:
Strong communication skills are essential for collaborating with cross-functional teams and conveying data-driven findings.
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