Summary
Daniel Klein is a Data Scientist based in New York with 14 years of experience bridging lab bench, servers, and decision-making to deliver practical, defensible analytic solutions. He blends computational, theoretical, and hands-on expertise to judge when methods that work at small sample sizes will scale to millions of observations. Comfortable diving quickly into new domains, he translates domain knowledge into models, algorithms, and statistical analyses that stakeholders can trust. His specialties include data analysis, statistical modeling, algorithm design, and mathematical modeling, with a focus on producing actionable, auditable results. Known for balancing rigor with pragmatism, he excels at turning complex experimental or operational data into clear decisions and scalable systems.
15 years of coding experience