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Data Science Subject Matter Expert - AI Evaluation (US-Remote)

Braintrust
Department:Data Analysis
Type:REMOTE
Region:San Francisco, CA
Location:San Francisco Bay Area
Experience:Entry level
Estimated Salary:$120,000 - $160,000
Skills:
DATA SCIENCEGENAILLMPROMPT ENGINEERINGDATA COLLECTIONFACT-CHECKINGBIAS MITIGATIONAI RESEARCHCONTENT DEVELOPMENT
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Job Description

Posted on: November 14, 2025

Job Description:

Seeking multiple Data Science Subject Matter Experts to help design, run, and optimize data collection and evaluation workflows for GenAI research.

You’ll translate high-level research needs into scalable processes, produce and curate challenging domain problems, and ensure factual, bias-aware, high-quality datasets for LLM training.

  • To Note: This is for an immediate project need. Project is approved for 3-months initially, with possibility to extend based on project/client demands.

Responsibilities:

  • Partner with GenAI researchers/engineers to capture data needs and success criteria.
  • Expand high-level requirements into clear, executable workflows for larger teams.
  • Execute collection/evaluation workflows rapidly with minimal supervision.
  • Innovate on workflows to maximize throughput and quality.
  • Collaborate cross-functionally to maintain quality at scale.
  • Conduct in-depth LLM-assisted research; gather reliable, up-to-date info.
  • Craft original, high-quality content and hard problems for LLM eval/train.
  • Perform rigorous fact-checking (precision/recall) to prevent misinformation.

Requirements:

  • Education: Master’s with distinction or PhD in Data Science; top-tier institution preferred. Significant domain experience considered.
  • Content development expertise across Data Science.
  • Exceptional writing: clear, concise, engaging; across formats.
  • Strong research & fact-checking; bias mitigation.
  • Originality/creativity; distinct human voice.
  • Detail orientation; precise data presentation; thorough proofreading.
  • Communication: articulate complex info; strong collaboration.
  • Understanding of AI/LLMs, their capabilities/limits.
  • Prompt engineering and familiarity with AI writing tools.
  • Ethical AI awareness and data literacy (collection, cleaning, transformation).
  • Thrives in fast-paced, minimally supervised environments.
Originally posted on LinkedIn

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