Vetted Data & Analytics Professionals in the NYC Metro

“Data/ML practitioner with hands-on experience building NLP systems from prototype to production: delivered a Twitter sentiment classifier with robust preprocessing, SVM modeling, and Power BI reporting, and built entity-resolution pipelines for messy multi-source customer data (reporting ~95% improvement in unique entity identification). Also implemented semantic linking/search using SBERT embeddings with FAISS vector retrieval and domain fine-tuning (reported ~15% precision lift), and applies production workflow best practices (Airflow/Prefect, Docker, Azure ML/Databricks, Great Expectations).”

“Applied ML to physical EV fleet systems at ST Labs, building a real-time CNN-LSTM fault prediction pipeline from streaming vehicle telemetry and addressing live data alignment issues via resampling/interpolation and buffered inference. Also developed a V2G/G2V energy transfer algorithm to automate charging/discharging for profit optimization, and made high-impact low-latency pipeline decisions at Astera Holdings using profiling, replay testing, and live A/B validation.”

“Sales/business development candidate with hands-on outbound experience across donor/partner and community stakeholder outreach, including multi-channel campaigns (email, word-of-mouth, door-to-door) managed through Salesforce. Applied data-driven targeting (NY census) to focus outreach on high-poverty areas and has experience operating in an early-stage/ambiguous environment at NBC during the Paris Olympics, using proactive coordination and meetings to create structure.”

“Built a production multimodal LLM-based vendor risk assessment platform that ingests SOC reports and other documents, uses a strict RAG pipeline with grounded evidence (page/paragraph citations), and dramatically reduces analyst review time. Experienced with LangGraph/LangChain/AutoGen for stateful, fault-tolerant agent workflows, and emphasizes reliability (schema validation, guardrails) plus low-latency delivery (~1–2s) through hybrid retrieval, reranking, caching, and model tiering.”

“LLM/ML engineer who has shipped production systems in legal/financial-risk domains at Wolters Kluwer, including a hybrid OCR+deterministic+LLM extraction pipeline that structured UCC filings at massive scale and drove $6M+ in revenue. Also built LangGraph-based multi-agent “Deep Research” workflows with model routing, tool calls (MCP), persistence, and human-in-the-loop review, and partnered closely with policy writers to deliver LLM summarization that cut writing time by ~60%.”

“GenAI/LLM engineer who recently built a production compliance assistant at State Farm for KYC/AML and regulatory teams, using AWS Bedrock + LangChain with Textract/Lambda pipelines to extract fields, tag risk, and summarize long documents. Implemented RAG, strict structured outputs, and human-in-the-loop guardrails, and reports automating ~80% of documentation work while reducing review time by ~40%.”