Hi — I’m Sarah’s RAG-based LLM agent. Ask me about her experience, projects, technical skills, or approach to production AI.
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Sarah D / Senior Data Scientist
Production AI across security and enterprise learning.
Experienced data scientist who has built AI for cybersecurity and enterprise learning. Her work spans feature engineering, model evaluation, data pipelines, AWS deployment, knowledge retrieval, telemetry, and product feedback.
Roles that fit my experience
Senior Data ScientistSenior Machine Learning EngineerApplied AI Engineer
Core strengths
- Model and feature design for varied data problems
- Production ML and recurring data pipelines
- RAG, semantic search, and knowledge systems
- Technical leadership across AI services
- Operational judgment under real constraints
Production experience
- Phishing detection pipelines for DNS traffic on AWS
- Ensemble modeling with character-level TF-IDF features
- Production RAG chatbot and generative AI services for Cisco U.
- Semantic search, knowledge retrieval, telemetry, and user feedback
- OpenSearch and S3 for state, artifacts, and workflows
Enterprise learning experience
- Cisco Learning & Development, 2023–2025
- Led the Cisco U. generative AI services team
- Two years building generative-AI services, including a production RAG chatbot on AWS (2023–2025)
- Semantic search and enterprise knowledge retrieval
- AI-service quality metrics and product feedback
Cybersecurity experience
- Cisco Talos security engineering, 2016–2023
- Phishing URL and domain detection
- Threat-intelligence data and reporting automation
- DNS, WHOIS, VirusTotal, and DGA signals
- Security-team collaboration and mitigation workflows
Key projects
- Live DemoAI Security Research Agent
- Case StudyML Phishing Domain Detection
- Live Demo RAG-based LLM portfolio agent
Production mindset
- Security and privacy boundaries
- Scalable architecture and cost controls
- Evaluation, logging, observability, and monitoring
- Graceful failure, versioning, and rollback
- Human review and feedback loops
Technical stack
A practical stack spanning applied AI, production systems, knowledge retrieval, analytics, and security.
AI + retrieval
RAGAI AgentsSemantic SearchKnowledge RetrievalPineconeOpenSearch
Machine learning
scikit-learnTF-IDFEnsemble ModelsFeature EngineeringModel Evaluation
Production systems
PythonSQLAWSDockerKubernetesPrometheusSentry
Security data
Threat IntelligencePhishing DetectionDNSWHOISVirusTotal