Data Science - AI Document Understanding, Co-op
Ancestry · Lehi, UT
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Jun 30, 2026
Lehi, UT
Jul 20, 2026
What this job asks for AI summary
Junior level · Remote · Part-time
“or” means any one of them counts — you don't need all of them.
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 950 people nationally plausibly meet what this posting asks for (data scientists). range 280–1,700
Applicant volume Light — Few people clear these requirements, so an application that does clear them gets looked at. Worth applying to even if you miss a nice-to-have.
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 (9)
This is a part-time, work-study co-op explicitly designed for active Master's or PhD students continuing their education in the fall — not a full-time hire. Seniority is set to Junior accordingly.
The posting says 'Master's or PhD preferred' but also accepts equivalent quantitative fields; no degree is hard-gated, so the degree requirement is set to None.
The role sits between Data Science (ML/NLP modeling, LLMs, agentic AI) and Software Development (building agentic systems, deploying pipelines); Data Scientists is the primary classification given the heavy ML/NLP research framing, with Software Developers as the runner-up.
Agentic frameworks (LangChain, LangGraph, CrewAI, AutoGen, AgentCore) are listed together as a single interchangeable requirement in the qualifications section; LangChain is used as the primary name with the others as alternatives.
Cloud platforms (GCP, AWS, Vertex AI, SageMaker, Bedrock, etc.) are explicitly called out as 'a plus' in the posting and are therefore marked as preferred.
Inference optimization techniques (vLLM, LoRA, QLoRA, quantization) appear in the qualifications section but with softer framing ('experience with'); marked preferred to reflect that context.
No compensation figures are provided in the posting.
Posting is for a part-time engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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