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Vetted Regression Analysis Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in generative AI and healthcare ML
Mid-level Data Analyst specializing in financial and healthcare analytics
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in Generative AI, NLP, and recommender systems
Mid-level Data Scientist specializing in ML, MLOps, and applied risk modeling
Mid-level Machine Learning Engineer specializing in MLOps and LLM/RAG systems
Mid-level Data Scientist specializing in ML, NLP, and forecasting across finance and retail
Mid-level Data Engineer specializing in cloud data platforms and BI analytics
Mid-level Data Engineer specializing in cloud data pipelines and analytics (AWS/Azure)
Mid-level Business Intelligence Engineer specializing in AI-powered analytics
Junior operations and analytics professional specializing in transportation and business analysis
Senior Data Scientist specializing in ML engineering and cloud analytics
Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Senior Full-Stack Software Engineer specializing in cloud, microservices, and AI
Senior Data Strategy & AI Product Consultant specializing in analytics platforms and privacy-safe measurement
Bharath Reddy Nallu
Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps
“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”
Likitha Kukunarapu
Mid-level Applied AI Engineer specializing in data engineering and healthcare AI
“Built production LLM agents spanning document Q&A, financial insight generation, and ERP-like operational data workflows, with a strong focus on reliability, grounding, and evaluation. Stands out for translating LLM systems into measurable business outcomes, including 70%–80% support workload reduction and a fallback-rate improvement from 18% to 8% through targeted RAG iteration.”
Vikas Katuru
Junior Full-Stack AI Engineer specializing in GenAI and secure data systems
“Backend-leaning full-stack engineer who has built AI-powered analytics products from 0→1, including a predictive analytics dashboard and an AI orchestrator for natural-language-to-database querying. Particularly strong in making LLM systems production-safe through schema validation, self-healing retries, monitoring, and retrieval optimization, with quantified impact on cost, latency, and quality.”
Shane Weinstock
Senior Data Scientist & Product Analytics Leader specializing in ML and experimentation
“Aspiring founder with ~15 years of experience across varied backgrounds, motivated by frustration with slow, change-resistant large organizations and a desire to bring innovative ideas to market. Familiar with how venture capital/accelerators function (though not directly worked in them) and expresses strong willingness to take entrepreneurial risks.”