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Vetted Data Scientists in the Greater Phoenix
Pre-screened and vetted in the Greater Phoenix.
Uma Patil
Mid-level Data Scientist specializing in ML, NLP, and LLM applications
Kyathi Puppaala
Mid-level Data Scientist/AI-ML Engineer specializing in LLMs, GenAI, NLP and MLOps
Priyanuj Bordoloi
Junior Data Scientist / ML Engineer specializing in LLMs and Computer Vision
“Currently working in CoRAL Lab, built and deployed IntegrityShield—a document-layer PDF watermarking system that keeps assessments visually identical while disrupting LLM-based solving; validated in a real classroom where it helped catch 12 AI-cheating cases. Also built MALDOC, a modular red-teaming platform for document-processing AI agents using LangGraph to run reproducible, deterministic adversarial trials across OCR/text/vision routes.”
SUMIT MAMTANI
Mid-level Data Scientist specializing in ML, MLOps, and customer analytics
“ML/NLP practitioner focused on insurance/claims analytics for a large financial firm, working with millions of fragmented structured and unstructured records. Built production-grade pipelines for entity extraction, entity resolution, and semantic search using Sentence-BERT + vector DB, including fine-tuning with contrastive learning (reported ~15% recall lift) and scalable ETL/containerized deployment on Kubernetes.”
Dhruv Madhwal
Mid-level Data Scientist specializing in LLMs, RAG systems, and applied ML
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.”
Krishna Rajput
Mid-level AI Engineer & Data Scientist specializing in LLMs, RAG, and multimodal systems
“LLM/GenAI engineer who built a production AI-powered credit risk policy summarization and compliance alerting platform at HCL Tech, focused on factual accuracy and auditability for a financial client. Implemented a multi-retriever LangChain RAG architecture with citations-only prompting, fallback agents, and human-in-the-loop legal review—cutting manual review time by 35% and scaling to 12 teams.”
Sameerjeet Singh Chhabra
Junior Robotics & ML Engineer specializing in simulation, control, and perception
“Robotics engineer focused on simulation, modeling, and control, with hands-on sim-to-real experience from a soft, foldable “grasshopper” robot where friction/contact physics and servo dynamics drove real-world performance gaps. Built a ROS 2 voice-operated TurtleBot system integrating YOLOv5 + stereo depth for object picking with an attached arm, and debugged AMCL/SLAM to cut localization error from 10–13 cm to ~5 cm. Currently developing a quadruped in MuJoCo with a 3-layer control stack (RL + MPC + PD) and an RL training pipeline in JAX ahead of hardware.”