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Vetted Data Scientists in the Greater Houston
Pre-screened and vetted in the Greater Houston.
Senior Generative AI Engineer and Data Scientist specializing in enterprise ML and RAG systems
Principal Data Scientist specializing in ML governance, healthcare and FinTech risk modeling
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
Senior Data Analyst & Data Scientist specializing in healthcare, epidemiology, and predictive modeling
Senior AI/ML Engineer specializing in LLMs, NLP, and production MLOps
Matthew Melendez
Mid-level Data Scientist specializing in machine learning and analytics
“Data scientist with hands-on experience building an XGBoost-based customer segmentation/churn risk scoring model used by sales and marketing teams. Emphasizes production-grade practices—efficient SQL for large-scale data pulls, rigorous data validation/testing, and scalable, modular Python code designed to support multiple customer types.”
Senior Data & ML Engineer specializing in cloud data platforms and real-time analytics
Senior Data Scientist specializing in fraud risk and real-time analytics
SaiGanesh Konagalla
Mid-level ML Engineer specializing in NLP and Generative AI
“Healthcare AI/ML engineer with Epic experience who built and deployed a HIPAA-compliant GPT-4 RAG clinical assistant over large medical document sets, emphasizing privacy controls and low-latency performance. Also automated end-to-end retraining and deployment of patient risk models using orchestration/CI-CD (Jenkins, SageMaker, MLflow), cutting deployment time from hours to minutes while improving reliability.”
Mid-level Data Scientist specializing in Generative AI, NLP, and computer vision
Mid-level Data Science & ML Engineer specializing in NLP, recommender systems, and MLOps
Senior Data Engineer/Data Scientist specializing in ML platforms, cloud data, and blockchain analytics
Varshitha Pendyala
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
“Built a production "Mini RAG Assistant" for internal document Q&A, focusing on grounded answers (anti-hallucination), retrieval quality, and latency/cost optimization. Uses LangChain/LangGraph for orchestration and applies a metrics-driven evaluation loop (including reranking and semantic chunking improvements) while collaborating closely with product stakeholders.”
Mid-level Data Scientist specializing in NLP, computer vision, and MLOps
Mid-level Applied AI Engineer specializing in LLM agents and RAG systems
Mid-level AI Engineer specializing in Generative AI agents and LLM production systems