Senior Life Sciences Knowledge Engineer Resume Ariya Palmer Senior Life Sciences Knowledge Engineer (919) 555-7316 ariya.palmer@example.com linkedin.com/example/ariyapalmer Raleigh, NC 27601 STRENGTHS Domain translation Turned clinical and regulatory questions into schemas and examples that gave technical teams clearer model targets. Evaluation judgment When models failed on edge cases, created focused slices and grader reviews that made next steps easier. Scientific collaboration Worked through ambiguous labeling decisions with experts, and became a trusted partner during difficult reviews. Audit discipline Kept provenance and licensing records connected to dataset decisions, giving reviewers a dependable evidence trail. Practical innovation Built MCP prototypes with technical partners, turning promising agent ideas into testable life sciences workflows. SKILLS Life Sciences Data Clinical Data Fine Tuning Data Generative AI LLMs Agents MCP Agentic Workflows Annotation Guidelines Task Taxonomy Output Schemas Human in Loop Evaluation Statistical Analysis Data Cleaning MLOps LANGUAGES English Native 40 Spanish Intermediate 20 MY CAREER 6.1 Years Senior Life Sciences Knowledge Engineer at Veridian Bioinformatics (2.5 Years) Knowledge Engineer, Life Sciences AI at BluePeak Clinical Data (1.6 Years) Biomedical Data Scientist at Carolina Translational Informatics Lab (2 Years) SUMMARY Senior life sciences knowledge engineer with six years building production grade clinical and biomedical datasets for AI enabled applications . Graduate training in biomedical sciences supports practical work across clinical, regulatory, and scientific data environments. Translates complex requirements into task taxonomies , output schemas, controlled vocabularies, annotation guidance, gold standard examples , and measurable model behaviors. Leads fine tuning dataset design, statistical analysis, data cleaning, preprocessing, provenance, licensing, and human in the loop evaluation . Partners closely with scientific experts, data scientists, machine learning engineers, and data engineers across proof of concept and production delivery. Hands on experience includes Generative AI, LLMs, MCP based agentic workflows, AWS, Azure DevOps, CI/CD, MLOps, GxP documentation, and production monitoring. Brings disciplined collaboration and domain judgment that can support reliable knowledge assets and useful life sciences products. EXPERIENCE Senior Life Sciences Knowledge Engineer Veridian Bioinformatics March 2024 - Present Raleigh, NC Owns knowledge engineering for clinical evidence and regulatory intelligence products, guiding dataset architecture, evaluation, agentic prototypes, and auditable delivery with scientific and technical partners. Defined clinical task taxonomies, output schemas , vocabularies, and gold standard examples for fine tuning. Trained 18 subject matter expert graders through calibration exercises and traceable annotation guidance. Diagnosed LLM failure modes through targeted slices and human in the loop evaluation rounds. Translated domain feedback into prompt, retrieval, schema, and tool call changes with data science partners. Maintained provenance, licensing, GxP, regulatory, and intellectual property records for auditable datasets. Connected grounded language models with approved services through MCP enabled agentic prototypes. Knowledge Engineer, Life Sciences AI BluePeak Clinical Data July 2022 - February 2024 Durham, NC Developed clinical and medical content datasets and cloud workflows, connecting structured publishing sources, evaluation practices, and controlled delivery from experimentation through monitoring. Built supervised fine tuning datasets from structured publishing sources and curated clinical examples. Applied statistical analysis , cleaning, and preprocessing to large biomedical datasets with reproducible transformation records. Resolved ambiguous clinical concepts with scientific and regulatory experts through labeling schema reviews. Created evaluation sets covering routine cases, edge conditions, and known model failure patterns. Implemented S3, SageMaker, Bedrock, ECS, and API Gateway workflows for controlled AI experimentation. Added Azure DevOps CI/CD checks for data artifacts, model handoffs, and production monitoring traceability. Biomedical Data Scientist Carolina Translational Informatics Lab June 2020 - June 2022 Chapel Hill, NC Curated translational research data and early machine learning studies, partnering with investigators and technical staff on analysis ready structures, reproducibility, and scientific review. Curated clinical research datasets across laboratory, phenotype, and study metadata for translational analyses. Applied reproducible cleaning and statistical checks to missingness, coding, outliers, and source discrepancies. Developed biomedical classification proofs of concept with documented assumptions, evaluation methods, and limitations. Created structured publishing templates and metadata conventions that improved reuse across research teams. Converted investigator questions into data specifications, evaluation plans, and interpretable analytical deliverables. Versioned provenance, transformations, and model experiments for auditable scientific review. PROJECTS Clinical Evidence Agent Workflow 2025 Built an MCP connected workflow that linked grounded language models with approved knowledge services for clinical evidence tasks, creating a monitored path from proof of concept to controlled evaluation. Biomedical Dataset Quality Framework 2023 Created reusable quality checks for cleaning, preprocessing, provenance, and evaluation across large biomedical datasets, helping analysts compare model iterations with consistent evidence. LEADERSHIP & AWARDS Recognized by scientific and technical peers for improving evaluator calibration and model feedback quality. Selected to lead cross functional proofs of concept connecting life sciences knowledge assets with agentic workflows. Received leadership recognition for maintaining auditable dataset provenance across regulated AI development. EDUCATION Master of Science in Biomedical Sciences University of North Carolina at Chapel Hill GPA: 4.0 2020 Chapel Hill, NC Coursework: Biomedical research, clinical data analysis, biostatistics, molecular biology Bachelor of Science in Biology North Carolina State University GPA: 4.0 2018 Raleigh, NC Coursework: Cell biology, genetics, biochemistry, research methods CERTIFICATIONS AWS Certified Machine Learning Specialty 2025 Azure DevOps and CI/CD for Machine Learning 2024 TECHNICAL SKILLS Life Sciences Data: Clinical data, Regulatory data, Biomedical datasets Generative AI: LLMs, Fine tuning, Model behavior Dataset Design: Input output pairs, Edge cases, Failure modes Taxonomy and Schemas: Task taxonomies, Output schemas, Controlled vocabularies Annotation Systems: Annotation guidelines, Labeling, Grader calibration Evaluation Methods: Human in the loop, Evaluation sets, Statistical analysis Data Engineering: Data cleaning, Preprocessing, Structured publishing AWS Machine Learning: S3, SageMaker, Bedrock AWS Application Services: ECS, API Gateway, Cloud deployment DevOps and MLOps: Azure DevOps, CI/CD, Production monitoring Agentic Systems: MCP, Tool calls, Agentic workflows Governance and Compliance: GxP, Dataset provenance, Licensing SKILLS Life Sciences Data Clinical Data Fine Tuning Data Generative AI LLMs Agents MCP Agentic Workflows Annotation Guidelines Task Taxonomy Output Schemas Human in Loop Evaluation Statistical Analysis Data Cleaning MLOps PROFESSIONAL AFFILIATIONS Life Sciences Knowledge Engineering community contributor, sharing practices across scientific and technical teams. Biomedical data science collaborator, building relationships across research, analytics, and machine learning groups. LANGUAGES English (Native) Spanish (Intermediate) ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. REFERENCES AVAILABLE ON REQUEST
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