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

This role focuses on designing, running, and optimizing data collection and evaluation workflows for GenAI research.

$75.00/hr – $90.00/hr

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.

To Note: Hourly rate range (75 – 90) is in USD per hour.

Responsibilities:

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• 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 evaluation/train.
  
• Perform rigorous fact‑checking (precision/recall) to prevent misinformation.
  

Requirements:

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• Education: Master’s with distinction or PhD in Data Science; top‑tier institution preferred. Significant domain experience considered.
  
• Detail orientation; precise data presentation; thorough proofreading.
  
• Communication: articulate complex info; strong collaboration.
  
• Understanding of AI/LLMs, their capabilities and 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.
  

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• Entry level
  

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• Full‑time
  

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• Engineering, Information Technology, and Science
  

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• Technology, Information and Internet, Data Infrastructure and Analytics, IT System Data Services