Vetted Data & Analytics Professionals in California

“LLM/agentic-systems builder who has shipped production tools for investment research and procurement insights, including a company screener that processes thousands of conference-listed companies using FireCrawl + Google Search + Gemini. Demonstrates strong orchestration expertise (LangGraph multi-agent graphs), performance optimization (async/batching to sub-30s), and pragmatic reliability/evaluation practices with stakeholder-friendly UX (real-time cost tracking and model/parameter toggles).”

“Performance marketing analyst at Meta supporting Amazon who identified Amazon app users as a high-value segment (2x ROAS), built and validated a retargeting audience via rigorous A/B testing, and helped drive a global rollout across thousands of campaigns resulting in ~$80M annual revenue. Strong in experiment design, SQL-driven insight generation, and translating performance learnings into cross-platform creative and catalog strategy.”

“ML/NLP practitioner and technical founder who built an AUP risk-scoring model at Bill.com using TF-IDF + SVD features with XGBoost, and previously created automated data-quality guardrails for a Global Equity Risk stacked ML model at Thomson Reuters. Recently built a RAG-based chatbot for PaymentJock’s Home Affordability Probability product using embeddings and a local vector database (FAISS/Chroma), improving answer quality through chunking rather than expensive fine-tuning.”

“Technology/architecture leader with Accenture experience delivering data- and AI/ML-driven products, including a legal contract search solution and customer sales analytics for AWS. Known for scaling distributed teams (onshore/offshore), making pragmatic architecture decisions, and solving hard data problems (proprietary sources, data quality) while implementing scalable integrations like Redshift-to-Salesforce via parallelized pipelines.”

“Senior Engineering Manager with large-scale platform/API ownership at eBay, leading a globally distributed team and redesigning Order public APIs used by external developer ecosystems at ~800M requests/day, delivering 84% performance gains and reducing compute by ~300 VMs. Also led Google CRES ETL migration work on GCP, creating reusable Python libraries to standardize configuration across 10 integrations and improve developer productivity.”

“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.”