KYEONGRIM SONG

EDUCATION Bachelor [of ***** Science, Wilshire Statistics Blvd] [Los Angeles, CA, 90024] [201-***-****] [ac8obu@r.postjobfree.com] University GPA: • 3.Related Computation Technologies 52 of coursework: California, and for Data Optimization Los Design Analysis, Angeles analytics for Time Statistics, Series experiment, Analysis Monte Statistical Carlo Methods, Models Python and Data and Mining Other December 2018 Completed Requirements for Transfer

College • • GPA: College of Alameda 3.8 Honors Society (Phi Theta Kappa) June 2016 SKILLS PROJECTS Department • • Technical Language of Proficiency: Proficiency: Statistics, UCLA Statistical Fluent in Korean Programming in R, Python, Advanced Microsoft Suites Kaggle • • • • Conducted Random Collaborated H1-Led Efficiently Competition B the visa project Forest, petition and complex on effectively team UCLA svm, a team success data to KNN, of conduct cleaning cleaned three with etc.) high and to analyses and data estimate designed accuracy. applied resulting and best summarized and statistical presenting classifier classification algorithms to project a the high models H1-insights performing (B logistic dataset. to predict in regression, a model. detailed and estimate report. Summer 2018 Statistical Consulting Project

• Teamed included relationships models for up classification higher with between six accuracy. students models predictors to on analyze major (Logistic and selection regression, predict in outcomes relation Pearson to on graduation chi-multiple squared, projects, rate, etc.identify ), and which fine tune

• Conducted complex data cleansing and merging for downstream modeling.

• Extracted new features to improve model accuracy.

• Provided assist student recommendations with major selection. to the admission office to improve student graduation rate and Spring 2018

• Data Presented Simulation actionable Project insights to a panel of professors and UCLA Admissions team.

• Coordinated using ANOVA. with a team of students to estimate effectiveness of different medical treatments

• Designed project. the experimental plan and prepared the sampling dataset to conduct the simulation

• Presented the optimal medical treatment combinations to the panel of professors. Winter 2018

Time • • Used including forecast Formulated Series a multivariate Project vector a report auto-time explaining regression, series to process SARIMA compare of modelling, analysis the accuracy and exponential summarizing of several smoothing, forecasting insights and into methods, a the consensus data set Fall 2018