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Vetted Data Scientists
Pre-screened and vetted.
Andrew Clayman
Senior Data Scientist specializing in ML, NLP, and production AI systems
“Machine learning/NLP engineer with deep Azure stack experience (Data Factory, Databricks/Spark, Delta Lake, Azure OpenAI, Azure AI Search) who built end-to-end production systems for semantic clustering, entity resolution, and hybrid search. Demonstrated measurable gains from embedding fine-tuning (~15% retrieval precision, ~10–12% nDCG@10) and designed scalable, quality-checked pipelines with MLOps best practices.”
Amit Gangane
Junior Data Scientist specializing in agentic AI and RAG pipelines
“LLM/agentic systems builder who shipped production workflows at Angel Flight West and Eureka AI, combining LangGraph + RAG (Postgres/pgvector) with strong observability (LangSmith/Langfuse). Delivered large operational gains (address lookup cut from 10 minutes to 60 seconds; accuracy to 92%) and has a track record of quickly stabilizing customer-critical pipelines (Pydantic-enforced JSON for ETL) while partnering with sales/ops to drive adoption.”
Pandraju Gamanapriya
Mid-level Data Scientist specializing in healthcare ML and GenAI
“Healthcare data/NLP practitioner with experience at UnitedHealthcare building production ML systems that connect unstructured call center transcripts and medical notes to structured claims data. Has delivered measurable impact (25% classification accuracy lift; ~30% relevance improvement) using classical NLP, embeddings (Sentence-BERT + FAISS), and AWS SageMaker deployments with robust validation and drift monitoring.”
PRAHARSHA JANDHYALA
Mid-level Data Scientist/Data Analyst specializing in ML, BI dashboards, and ETL pipelines
“Data/ML practitioner with experience at Humana and Hexaware, focused on turning messy, semi-structured datasets into production-ready pipelines. Built an age-prediction model from book ratings using heavy feature engineering and multiple regression models, and has hands-on entity resolution (deterministic + fuzzy matching) plus embeddings/vector DB approaches for linking and search relevance.”
Mid-level Data Scientist & AI/ML Engineer specializing in GenAI, NLP, and predictive modeling
Mid-level Data Scientist specializing in ML, NLP, and cloud data platforms
Mid-level Data Scientist specializing in AI/ML for healthcare analytics
Mid-level Machine Learning Engineer specializing in NLP and recommender systems
Mid-level Machine Learning Engineer specializing in LLMs, semantic search, and distributed data pipelines
Mid-level Data Scientist specializing in LLMs, RAG, and ML systems
Mid-level Data Scientist specializing in Generative AI, LLMs, and MLOps
Mid-level Data Scientist specializing in ML, NLP, and MLOps for finance and healthcare
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
Senior Software Engineer specializing in real-time systems, IoT, and game development
Mid-level Data Scientist specializing in healthcare and fraud analytics with GenAI/LLM expertise
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
Mid-level Data Scientist specializing in Generative AI, NLP, and computer vision
Mid-level Data Scientist specializing in ML, NLP, and Generative AI on cloud platforms
Mid-level AI/ML & Generative AI Engineer specializing in LLMs and MLOps
Mid-level Machine Learning Engineer specializing in LLMs and scalable RAG systems
Junior AI/ML Engineer specializing in NLP, computer vision, and LLMs