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Vetted Data Science Professionals
Pre-screened and vetted.
Staff Software Engineer specializing in Healthcare IT and FinTech platforms
Mid-level Machine Learning & Biostatistics professional specializing in healthcare AI
Staff/Lead AI Engineer specializing in LLMOps, RAG, and Azure-based ML platforms
Intern-level Software/ML Engineer specializing in AI, data science, and full-stack development
Senior Cloud Solutions Architect specializing in AWS/Azure, security, and hybrid cloud
Director-level technology leader specializing in data, AI, automation, and digital transformation
Executive product leader specializing in Healthcare IT and SaaS growth
Senior Python/ML Engineer specializing in LLM-powered backend systems
Executive Technology Leader specializing in AI, FinTech, and data analytics
Junior Full-Stack Software Engineer specializing in ML, cloud infrastructure, and LLM agents
Mid-level Data Scientist specializing in causal inference and data engineering
Director-level Product Data Science leader specializing in experimentation and causal inference
Engineering Leader specializing in growth platforms and transaction systems
Intern AI/Software Engineer specializing in LLM agents and full-stack automation
Junior AI Product Engineer specializing in LLM workflows and analytics automation
Executive CTO/CPO and Product & Technology Leader specializing in Healthcare SaaS and AI/ML
Senior Business Analyst specializing in small business lending and portfolio risk
Director of Engineering specializing in AI/ML, data platforms, and consumer messaging
Executive product and engineering leader specializing in FinTech and healthcare technology
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
Harinee Mohanakrishnan
Junior AI/ML & Cloud Software Engineer specializing in LLM applications
“AI engineer (2+ years; pursuing an online MS at UIUC) who has shipped an AI-powered voice screening platform end-to-end on GCP with strong production monitoring and measurable hiring-process impact (80% reduction in unqualified pass-through; ~50+ hours saved per role). Also built and deployed an AWS-based context-aware hybrid search system using OpenSearch as a vector store, and has hands-on experience with multi-agent LLM orchestration (ReAct) and structured-output guardrails.”