{"id":3239142,"url":"https://alion.io/job/micro1-data-science-analytic-methodology-sme","title":"Data Science & Analytic Methodology SME","company":{"id":13196,"name":"micro1","domain":"micro1.ai","url":"https://alion.io/company/micro1","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"worldwide","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[],"status":"live","first_seen_at":"2026-10-23T09:23:14Z","employer_posted_date":null,"last_verified_at":"2026-10-23T09:23:14Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"Role Title: Data Science & Analytic Methodology SME\nRole Type: ContractorLocation: Remotemicro1 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.\nScope of Work\nMap scaled-analysis and pipeline-integration scenarios to an established taxonomy across key evaluation areas.\n\nAuthor 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.\n\nEvaluate and grade responses based on criteria such as source handling, reasoning, understanding of limitations, and practical utility.\n\nIdentify and flag instances of model over-refusal that could hinder legitimate analytic workflows or disrupt pipeline continuity.\n\nDocument challenging edge cases, emerging methodology concerns, and provide actionable recommendations for continuous improvement.\n\nContribute clear, insightful written and verbal feedback that supports iterative, high-quality project outcomes.\n\nPreferred Qualifications\nDemonstrated experience integrating LLMs—such as government GPT variants—into complex data or analytic pipelines.\n\nProven capability in conducting analysis at scale, with an understanding of automation failure modes and relevant evaluation metrics.\n\nTrack record of teaching, mentoring, or technical leadership in data science or related analytic disciplines.\n\nExpertise in authoring clear, concise technical documentation and conveying complex concepts through strong written English.\n\nExposure to the design of evaluation frameworks or benchmark systems.\n\nFamiliarity with defense, intelligence, or government analytic domains is highly valued.\n\nAbility to operate effectively in distributed, international project environments with minimal clearance constraints.\n\nOriginally posted on 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