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Vetted Data Scientists in Texas
Pre-screened and vetted in Texas.
Mid-level Data Scientist specializing in ML, MLOps, and LLM fine-tuning
Mid-level Data Scientist specializing in financial ML, forecasting, and NLP/GenAI
Intern Data Scientist specializing in ML, MLOps, and Generative AI analytics
Mid-level AI/ML Engineer specializing in MLOps, RAG, and production NLP
Mid-level Data Scientist specializing in MLOps, NLP, and Generative AI
Senior Data Scientist specializing in ML, analytics, and cloud data platforms
Senior Generative AI Engineer and Data Scientist specializing in enterprise ML and RAG systems
Mid-level Data Scientist specializing in LLMs, RAG systems, and production MLOps
Principal Data Scientist specializing in ML governance, healthcare and FinTech risk modeling
Mid-level Data Scientist specializing in fraud detection and scalable ML systems
Senior Data Scientist specializing in LLM-powered NLP, recommender systems, and anomaly detection
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and multi-agent systems
Senior Data Scientist / ML Engineer specializing in NLP and Generative AI
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Senior Data Scientist specializing in ML, fraud risk, and Generative AI (RAG/LLMs)
Anurag Reddy
Mid-level Data Scientist specializing in ML, MLOps, and Generative AI
“ML/NLP engineer who built a RAG-based technical assistant for Caterpillar field engineers, transforming PDF keyword search into intent-based semantic retrieval across manuals, logs, sensor reports, and technician notes. Strong in productionizing data/ML systems (Airflow, PySpark) with rigorous preprocessing, entity resolution, and evaluation—delivering measurable gains in accuracy, relevance, and duplicate reduction.”
Duncan Freeman
Staff Machine Learning Engineer specializing in NLP, LLMs, and document intelligence
“ML/AI engineer at PNC who has shipped enterprise-grade RAG and document intelligence systems for compliance and policy workflows. Stands out for combining LLM product thinking with production rigor—owning FastAPI/Kubernetes deployments, monitoring, evaluation, and human-feedback loops that drove measurable gains like 40% faster policy search and 30% faster compliance review.”
Sujeeth Rajkumar
Mid-level Generative AI Engineer specializing in LLMs and enterprise AI
“Built and owned an enterprise LLM/RAG document intelligence platform for PNC Financial Services in a compliance-heavy environment, focused on grounded answers over internal finance and policy documents. Stands out for combining GenAI product delivery with production engineering discipline, delivering 60% faster document review and materially better answer quality while creating reusable FastAPI-based AI services for multiple teams.”
Jaideep bommidi
Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps
“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”
Ashwitha E
Junior Data Scientist specializing in fraud analytics and cloud data platforms
“Built and deployed production LLM-powered document summarization/classification systems using embeddings, vector databases (RAG-style retrieval), and automated evaluation (BERTScore/ROUGE), with a focus on monitoring and scalable cloud pipelines. Also partnered with a fraud analytics team to deliver a transaction anomaly detection solution, translating model outputs into Power BI dashboards and actionable KPIs while iterating on thresholds and alerts based on stakeholder feedback.”