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Ian McNabb
Systemic Systematic Wordsmith ★ Statistical Analyst, Scientific Data Analyst, Data Scientist, Data Visualization, Pipeline Engineer, Quantitative Research Analyst
Ian McNabb is a data analyst specializing in complex systems, particularly in analyzing chemical abundance issues within nebulae. He excels in creating and optimizing pipelines to extract insights from datasets through statistical analyses. With a bottom-up approach, Ian can effectively communicate intricate systemic problems in easy-to-understand terms from an outlier's perspective. Describing himself as efficient, inquisitive, and logical, he holds an INTJ-A (Architect) personality. Ian's research experience includes working with Bayesian statistics, linear regression, least-squares minimization, and k-clustering.
Ian McNabb's educational background includes a Doctor of Philosophy in Physics, Astrophysics, Philosophy from Peking University, a Masters in Astronomy, Physics from the University of Denver, and a Bachelor of Science in Astronomy, Physics from Franklin & Marshall College. He also studied at Los Gatos High School.
In terms of professional experience, Ian has held positions as a Research Assistant and Data Analyst. He has also been affiliated with prestigious organizations such as the Institute for Astronomy and Astrophysics as a former Doctoral Candidate, the NASA Ames Research Center as a former Research Assistant, and the Spitzer Science Center at Caltech as a former Visiting Research Scholar.
Ian McNabb is open to opportunities in roles such as Statistical Analyst, Scientific Data Analyst, Data Scientist, Data Visualization Expert, Pipeline Engineer, and Quantitative Research Analyst. He is well-versed in programming languages such as Python, RStats, and SQL. Ian can be contacted via email at imcnabb42@gmail.com and is open to collaborations in the fields of data analysis, research, and consulting.
A firm believer in the universality of science, Ian McNabb operates with the motto 'Science is universal; opinions are ubiquitous.' He is recognized for his expertise in bottom-up analysis, data insights, statistical modeling, and small data analysis for startups and established organizations alike.