Why This Role Stands Out
This role offers a unique opportunity to drive impactful advancements in LLM quality and RAG pipelines, perfect for a data scientist eager to own projects end-to-end. You'll thrive here if you enjoy deep technical challenges, developing innovative solutions, and contributing to critical national security initiatives. Apply now to leverage your expertise and grow your career in a dynamic environment.
Quick Overview
Job Description
OVERVIEW: As the Data Scientist, you will report to the onsite Project Team leader and work closely with a small exercise support team. You will own problems end-to-end, to include designing evaluation frameworks, improving prompts and retrieval pipelines, analyzing interview data, and shipping measurable improvements into production.
GENERAL DUTIES: LLM Quality & Evaluation
- Improve prompting strategies and structured outputs across reporting formats * including law enforcement, intelligence, after-action, interview summaries, and * survey analysis
- Design evaluation sets, scoring rubrics, and automated evaluation pipelines
- (including LLM-as-judge approaches) for relevance, coherence, completeness, * and error modes
- Reduce hallucinations and improve traceability and attribution RAG & Knowledge Pipelines
- Build and iterate on RAG pipelines, curated knowledge packs, and question-tree * triggers
- Create and maintain base datasets (follow-up triggers, Essential Elements of
- Information/Critical Information Requirements, glossaries, watchlist cues) with * versioning and documentation
- Tune retrieval and reranking to perform reliably under edge constraints (limited * compute, memory, and connectivity) Interview Analytics
- Analyze transcripts to surface evasiveness, inconsistencies, and actionable leads
- Develop labeling strategies, analytic rubrics, and ground-truth datasets
- Conduct quantitative and qualitative analysis of interview data to identify patterns * and support operational decisions Measurement & Documentation
- Build lightweight dashboards and metrics for model performance and field * reliability
- Document methods and maintain audit trails so outputs remain defensible for * government end users
- Partner with engineering to validate and ship improvements into production REQUIRED QUALIFICATIONS:
- 2-5 years of applied data science or NLP experience
- Strong Python skills (pandas, NumPy, scikit-learn) with comfort standing up * experiments and pipelines
- Hands-on experience with LLMs: prompt engineering, output evaluation, safety, * and quality controls
- Experience with unstructured text data - cleaning, labeling, building evaluation * metrics
- Proficiency in data analysis, reporting, and visualization for technical and non- * technical audiences
- Ability to work on-site in the El Paso / Las Cruces / WSMR area DESIRED QUALIFICATIONS:
- RAG implementation experience (vector databases, embeddings, reranking)
- Experience with structured evaluation frameworks (RAGAS, custom LLM-as- * judge, or equivalent)
- Familiarity with edge or offline deployment constraints
- Exposure to interview analytics, structured debriefing, structured reporting, or
- HUMINT-adjacent workflows
- Experience delivering in classified or regulated environments CLEARANCE:
- Active Secret clearance
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