Vetted Data & Analytics Professionals

“Deloitte consultant who led cross-functional teams delivering a Snowflake/AWS data ingestion, warehousing, and analytics platform, with a strong track record of executive alignment and risk mitigation. Built reusable business-development accelerators (including an end-to-end Appian app and a Java integration-config tool) credited with helping secure $75M+ in contracts, and has high-confidentiality experience consulting for DoD and FDA.”

“Built and shipped a production agentic LLM tool that helps internal teams update technical product whitepapers using plain-language edit requests, with strong guardrails (citations, verification, refusal/clarify flows) to reduce hallucinations and maintain compliance. Experienced taking LLM workflows from rapid LangChain prototypes to more predictable, debuggable LangGraph agent graphs, and orchestrating end-to-end ingestion/embedding/indexing/eval/deploy pipelines with Kubeflow.”

“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”

“Built and deployed a healthcare NLP application that used an LLM-style physician interface feeding a random forest model to predict treatment plans for hard-to-triage patient subgroups, backed by a Databricks medallion pipeline and heavy feature engineering to address missing/low-integrity data across ~50K patients. Also delivered an earlier Microsoft AI Builder automation that improved transportation bill payment workflows by training non-technical payroll/procurement teams to use automated outstanding-payables reporting.”

“Atlassian ML/AI engineer who has shipped end-to-end production systems combining classical ML, streaming infrastructure, and LLM-based personalization to improve onboarding and free-to-paid conversion. Particularly strong in turning research-style RAG and reranking ideas into low-latency, reliable product systems with robust evaluation, safety guardrails, and reusable platform services for other teams.”

“Data science/NLP practitioner with experience at NVIDIA and Microsoft building production-grade NLP and data-linking systems. Has delivered high-performing pipelines (e.g., F1 0.92) and large-scale entity resolution (F1 0.89), plus semantic search using embeddings and Pinecone with ~30–40% relevance gains, backed by rigorous validation (A/B tests, ROUGE, MRR) and strong MLOps/workflow tooling (Airflow, Databricks, FastAPI, MLflow, Prometheus/ELK).”