micro1
Data Science & Analytic Methodology SME
- Where
- Remote, worldwide
- Salary
- Not stated
- Level
- Senior
- Employment
- Contract
- Field
- Data & analytics
- Posted
- 22 d ago
The role at a glance
micro1 is engaging Data Science & Analytic Methodology SMEs to contribute expertise to a customer's high-impact project focused on advanced analytic pipelines and large language models (LLMs).
Who can apply
The location field says: Worldwide
(Himalayas)
About the job
Role Title: Data Science & Analytic Methodology SME
Role Type: Contractor
Location: Remote
micro1 is engaging Data Science & Analytic Methodology SMEs to contribute expertise to a customer's high-impact project focused on advanced analytic pipelines and large language models (LLMs). In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
- Map scaled-analysis and pipeline-integration scenarios to an established taxonomy across key evaluation areas.
- Author detailed analytic cases that reflect authentic deployment patterns, including automated triage, enrichment, and analysis-at-scale, as well as representative failure modes in real-world settings.
- Evaluate and grade responses based on criteria such as source handling, reasoning, understanding of limitations, and practical utility.
- Identify and flag instances of model over-refusal that could hinder legitimate analytic workflows or disrupt pipeline continuity.
- Document challenging edge cases, emerging methodology concerns, and provide actionable recommendations for continuous improvement.
- Contribute clear, insightful written and verbal feedback that supports iterative, high-quality project outcomes.
Preferred Qualifications
- Demonstrated experience integrating LLMs—such as government GPT variants—into complex data or analytic pipelines.
- Proven capability in conducting analysis at scale, with an understanding of automation failure modes and relevant evaluation metrics.
- Track record of teaching, mentoring, or technical leadership in data science or related analytic disciplines.
- Expertise in authoring clear, concise technical documentation and conveying complex concepts through strong written English.
- Exposure to the design of evaluation frameworks or benchmark systems.
- Familiarity with defense, intelligence, or government analytic domains is highly valued.
- Ability to operate effectively in distributed, international project environments with minimal clearance constraints.
Originally posted on Himalayas
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