Senior Data Scientist
Norstella · Richmond, VA
—
Jul 24, 2026
Richmond, VA
Jul 25, 2026
What this job asks for AI summary
A senior individual-contributor role on a pharma-intelligence data science team, focused on researching, building, and shipping AI/ML solutions — such as agentic systems, RAG pipelines, and classical ML models — as production microservices. The work spans the full arc from identifying opportunities and prototyping to deployment, with one major product release owned at a time. Suits an experienced practitioner comfortable with LLMs, Python, and cross-functional collaboration, ideally with healthcare or pharma domain exposure.
Senior level · 5+ years · Remote · Full-time
Posted 12 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 770 people nationally plausibly meet what this posting asks for (data scientists). range 460–1,150
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The degree requirement states 'Graduate degree in a STEM field… or equivalent practical experience' — because equivalent experience is explicitly accepted, no formal degree is hard-gated.
The 5+ years figure is stated specifically for 'developing AI/ML applications and data driven solutions', which maps to the overall role-level experience requirement.
LangChain appears in the required qualifications alongside pandas and scikit-learn as an example of 'core data science libraries'; it is treated as a hard gate despite the 'etc.' qualifier, consistent with its placement in the Requirements section.
LLMs, RAG, and prompt engineering are listed together in the Requirements section under a single bullet; all are captured as required skills.
Agentic AI systems and MCP servers are mentioned both in the role narrative (as examples of past approaches) and under Preferred Qualifications ('Deep expertise in engineering agentic AI systems'); they are marked preferred, sourced from the Preferred section.
AWS sub-services (ECS, Bedrock, SageMaker, serverless) appear exclusively under Preferred Qualifications and are marked preferred accordingly.
The role is fully remote within the United States; no metro area is specified.
Read the full posting
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