eGig
Data Science & Analytic Methodology SME
micro1 · Remote · Posted 5h ago
This job was posted on Himalayas, an open job board. Join eGig free to get the apply link: every job you apply to is then kept in My applications, with the pay shown up front.
Salary$60 – $100 / hr
Experience5+ years
Job typeContract
Work modeRemote
Openings1
Apply by 22 Dec 2026
About the job
Role Title: Data Science & Analytic Methodology SMERole 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