Yue Yang

Intern Data Scientist specializing in GenAI (LLMs, RAG) and ML model optimization

Sunnyvale, CATechnical-Engineer Intern(Machine Learning), Technology & Product Development Group (TPG)1 years experienceInternSemiconductorsTechnologyConsulting

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About

Built and deployed a production LLM-powered risk assistant for KPMG and Freddie Mac that lets analysts query a confidential Neo4j risk graph in natural language (no Cypher), turning multi-day analysis into minutes with traceable, cited answers. Implemented rigorous guardrails, deterministic verification, RBAC/security controls, and a full eval/observability stack, cutting query error rate by ~50% and iterating through weekly UAT with non-technical risk analysts.

Experience

Technical-Engineer Intern(Machine Learning), Technology & Product Development Group (TPG)Synopsys

GenerativeAI Capstone Group LeadKPMG x Columbia University, Data Science Institute

Generative AI InternMusicNBrain

Education

Columbia Universitymaster, Data Science (2025)

University of California, Los Angelesbachelor, Applied Math (2024)

Key Strengths

Deployed production LLM risk assistant over confidential risk data for KPMG/Freddie Mac
Graph + LLM architecture enabling natural-language querying of Neo4j without Cypher
Strong hallucination/accuracy mitigation (schema maps, cite-or-drop, deterministic verification, numeric self-checks)
Built robust reliability/performance features (RBAC, sanitization, rate-limit handling, retries/backoff, caching) in locked-down environments
End-to-end observability and evaluation practice (latency P50/P95, token/cost logs, error taxonomy, prompt/version tracking, offline+online evals)
Quantified impact: reduced multi-day manual workflow to minutes; cut query error rate by ~50%
Effective collaboration with non-technical stakeholders via whiteboarding intents, success metrics, and weekly UAT iterations

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Contact

candidate@example.com(555) 123-4567LinkedIn Profile

Languages

English

Skills

Generative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Machine LearningDeep LearningData ScienceSoftware EngineeringScalable AlgorithmsNatural Language Processing (NLP)Data ModelingData AnalysisData VisualizationModel QuantizationModel PruningLatency Profiling