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Vetted Regression Analysis Professionals
Pre-screened and vetted.
Elizabeth Thorndike
Principal Performance Marketing & Growth Strategist specializing in paid search and video
“18-year Google veteran who managed and grew top customer investments, including Rocket Mortgage’s Google Search program—scaling spend from ~$60M/year to $170M/year. Led adoption of ROAS bidding and broad match through rigorous experimentation and forecasting, driving an additional $14.5M spend in 1H 2024 despite a challenging mortgage market.”
Senior AI Engineer specializing in LLMs, RAG, and production ML systems
Junior Software Engineer specializing in AI/ML and recommendation systems
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and scalable inference
Craig Leathers
Staff Data Analytics Lead / Data Scientist specializing in manufacturing process control
“Intel veteran who applied multiple linear regression and time-series drift analysis to semiconductor lithography overlay/metrology data, feeding model outputs into automated process control. Comfortable working across Python, VBA, and JMP/JSL, with a pragmatic approach to validation (RMSE + trend visualization) and data quality via close coordination with measurement/metrology teams.”
Jingfei Xu
Intern/Junior Software Engineer specializing in AI/ML and cloud-based systems
“Embedded/robotics software engineer with Hyundai Motors experience who owned an AI-driven perception validation pipeline using a Transformer-based approach to generate stable synthetic in-cabin audio for autonomy/ASR testing, cutting downstream testing time by 50%+. Has hands-on ROS integration (IMU sensor streaming, inference, control nodes), MQTT-based distributed messaging, and cloud/container deployment experience (Docker, Node/Express, AWS, CI/CD).”
Sason Torosean
Principal Data Scientist specializing in financial risk, forecasting, and applied ML
“ML/NLP practitioner and technical founder who built an AUP risk-scoring model at Bill.com using TF-IDF + SVD features with XGBoost, and previously created automated data-quality guardrails for a Global Equity Risk stacked ML model at Thomson Reuters. Recently built a RAG-based chatbot for PaymentJock’s Home Affordability Probability product using embeddings and a local vector database (FAISS/Chroma), improving answer quality through chunking rather than expensive fine-tuning.”
Jackson Spilka
Senior Strategy & Analytics Lead specializing in AI, media, and sports analytics
“Chief of Staff to the COO / Strategy & Business Development leader at Annapurna who unified four distinct entertainment verticals (film, TV, interactive, theatre) into the company’s first cross-functional five-year plan. Built standardized pipeline reporting, forecasting models grounded in real execution rates, and executive dashboards that improved decision-making speed and COO leverage while navigating creative/finance tension and sensitive information.”
Mid-level Data Scientist specializing in NLP, MLOps, and semiconductor manufacturing analytics
Senior Data Scientist specializing in NLP, LLMs, and Generative AI automation
Junior Research Engineer specializing in robotics, computer vision, and machine learning
Intern Software Engineer specializing in data engineering and LLM evaluation
Senior Data Scientist specializing in large-scale ML systems and recommendations
Junior Data Analyst specializing in experimentation, data quality, and ML analytics
Umar Ali
Mid-level Data Analyst specializing in econometrics, ESG, and labor market research
Dennis Noto
Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization
“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Principal Data Scientist specializing in ML, NLP, and forecasting for marketing and supply chain
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Mid-level Data Scientist specializing in ML for healthcare and strategy analytics
Gabrielle Burns
Senior AI/ML Engineer specializing in computer vision, NLP, and enterprise ML systems
“ML/AI engineer with hands-on ownership of production computer vision and GenAI systems, spanning real-time public safety video analytics and RAG-based knowledge assistants. Stands out for translating research-oriented approaches into scalable, monitored production systems with clear business impact, including 50% latency reductions, 25% faster response times, and 40% lower document search time.”
Krishna Sahith Poruri
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
“ML/LLM engineer who built a production RAG system (GPT-4 + FAISS + FastAPI) to deliver fast, grounded answers from proprietary documents, optimizing for sub-200ms latency and high-concurrency scale. Strong MLOps/observability background: drift monitoring with Prometheus + Streamlit, automated retraining via Airflow, Kubernetes autoscaling, and MLflow-managed model lifecycle, plus inference cost reduction through quantization and structured pruning.”