Data Science:• feature engineering• algorithm development• deep dives/root cause analysisSkills:• Machine Learning: gradient boosted trees, random forest, logistic regression, SVM,K-means, PCA, collaborative filtering, matrix factorization, isolation forest, NLP.• Software: Python (numpy, pandas, scipy, scikit-learn, nltk); Scope/Cosmos big dataplatform; MATLAB/Octave, Interactive Data Language (IDL); scripting in bash, Perl,csh; VBA, SQL; administration of linux-based work-stations; Keras-TensorFlow;familiarity with AWS, Caffe, C#, R, Spark, Hadoop, Ruby, MapReduce, Scala.• Collaboration: worked cooperatively with colleagues on most of research projects.• Communication: able to convey complex ideas to audiences spanning wide rangesof expertise: presented high-level results from research at many internationalconferences; also, as course instructor and teacher, conveyedprinciples of physics at basic levels to college and high school students.• Supervision/Mentoring: supervised undergraduate students, provided guidance for post-docs and junior research staff• Work Review: conducted peer review for journals and granting agencies; rigorously assessed claims made, and identified important, unstated issuesResearch Experience:• 15 years data analysis of spacecraft plasma and field measurements from several NASA and ESA missions• Scientific Modeling: developed computer simulations (particle-in-cell andmagnetohydrodynamics codes) to test physical models against data.• Writing: authored/co-authored 49 articles published in international, peer-reviewedjournals, as well as several successful grant proposals and grant extensions.Teaching Experience:• As graduate student, taught undergraduate laboratories, and problem review sections• Taught 10th grade physics for two years