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Vetted Random Forest Professionals
Pre-screened and vetted.
Mid-level Data Scientist specializing in LLMs and NLP for financial analytics
Mid-level Data Scientist specializing in healthcare and financial risk modeling
Senior Data Scientist specializing in machine learning and cloud analytics
Mid-level Data Scientist specializing in NLP, time-series forecasting, and GenAI
Mid-level Data Analyst specializing in ML, AI, and data visualization
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and NLP
Senior Data Scientist specializing in AWS ML solutions for healthcare, telecom, and e-commerce
Senior AI/ML & Data Science professional specializing in NLP, LLMs, and MLOps
Mid-Level Generative AI Engineer specializing in LLM apps, RAG, and cloud deployment
Mid-level Data Scientist specializing in ML, NLP, and cloud deployment
Senior AI/ML Engineer specializing in LLMs, NLP, and production MLOps
Mid-level Data Scientist / ML Engineer specializing in NLP, GenAI, and cloud ML deployment
Pravallika Kilari
Mid-level AI/ML Engineer specializing in NLP, GenAI, and MLOps in healthcare and finance
“AI/ML engineer with CVS Health experience deploying production LLM systems in regulated healthcare settings, including a large-scale RAG solution (1M+ documents) built for compliance-grade, auditable policy/regulatory Q&A with strong anti-hallucination controls. Also delivered an NLP summarization system for physician notes/case narratives by partnering closely with non-technical care operations stakeholders and iterating via prototypes, dashboards, and feedback loops.”
Venkatesh Nagubandi
Mid-level Software Engineer specializing in ML, LLM apps, and cloud data systems
“Built a production SQL chatbot for access-log analytics that replaced manual custom report requests with natural-language querying, using LangGraph and a ChromaDB-backed RAG pipeline for grounded, consistent answers. Implemented a privacy-preserving design where the LLM never sees raw customer data (only query metadata) and has experience building multi-agent/tool-calling systems with LangGraph (DeepAgents), including solving sub-agent communication drift via self-reflection.”
Chandan Chalumuri
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
“Data engineering / ML practitioner with experience at MetLife building transformer-based sentiment analysis over large unstructured datasets and productionizing pipelines with Airflow/PySpark/Hadoop (reported 52% efficiency gain). Also implemented embedding-based semantic search using Pinecone/Weaviate to improve retrieval relevance and enable RAG for customer support and document matching use cases.”