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Vetted Data Scientists
Pre-screened and vetted.
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.”
Dimple Galla
Mid-level Data Scientist / AI-ML Engineer specializing in RAG, MLOps, and real-time analytics
“Software/ML engineer who built a production automated job-finding and cold-email personalization system for Fortune 500 outreach, using JobSpy for dynamic scraping, LangChain orchestration, and LLM+vector DB semantic search with grounding/relevance metrics and guardrails. Also delivered a predictive investment analytics platform for financial advisors, communicating results via Tableau dashboards and portfolio KPIs like Sharpe ratio and drawdowns.”
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.”
Patrick Seeman
Mid-level Data Scientist and Game Tech Leader specializing in ML, healthcare analytics, and Unity
“Data scientist at Cleveland Clinic Taussig Cancer Institute who led a production automation to convert unstructured (and sometimes image-based) pathology reports into structured data for government reporting. Built an on-prem LangGraph + Ollama pipeline with OCR (Tesseract), spell-checking, confidence scoring, and human-audited guardrails to mitigate hallucinations and improve reliability under PHI constraints.”
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.”
Arslan Javed
Senior Machine Learning Engineer specializing in LLMs, NLP, and computer vision
“Built and owned production GenAI systems for both infrastructure automation and customer support. Most notably, they created a self-healing multi-cloud incident response system that automated 65% of tier-1 alerts and reduced application crashes by 75%, and also shipped a hybrid RAG support triage agent that automated 60% of tier-1 inquiries with human escalation guardrails.”
“Built and owned a production RAG-based conversational AI system at Entera for real estate analysis, taking it from experimentation through AWS deployment, monitoring, and iterative improvement. Demonstrates strong practical judgment in retrieval design, LLM safety, and scalable Python service architecture, with measurable impact including 30-40% reduction in manual analysis time and roughly 30% better response accuracy.”
Mid-level Data Scientist & AI/ML Engineer specializing in GenAI, NLP, and predictive modeling
Mid-level Data Scientist specializing in AI/ML for healthcare analytics
Mid-level Data Scientist specializing in ML, NLP, and cloud data platforms
Mid-level Machine Learning Engineer specializing in LLMs, semantic search, and distributed data pipelines
Mid-level Machine Learning Engineer specializing in NLP and recommender systems
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 Generative AI
Mid-level Data Scientist specializing in ML, NLP, and MLOps for finance and healthcare
Senior Software Engineer specializing in real-time systems, IoT, and game development
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
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