Data Scientist

David E. Martinez

**** *. *** ** #* Long Beach, CA 90814 714-***-**** *****************@*****.*** EDUCATION

University of California, Los Angeles

Bachelor of Science in Statistics June 2017

• Major GPA: 3.56

• Relevant Coursework: Computational Methods, Statistical Models and Data Mining, Analysis and Regression, Design and Analysis of Experiments, Programming with R, SPSS, STATA, SAS EXPERIENCE

Onsite Tutor, Math and English

LONG BEACH CITY COLLEGE, Long Beach, California 2015 – 2017 ORANGE COAST COLLEGE, Costa Mesa, California 2014 – 2016

• Established trust and ongoing relationships with students, resulting in improvements of up to 50% in test scores

• Guided students representing all backgrounds, ages, and abilities through challenges, beginning with basic arithmetic and continuing through higher level math, to include calculus and statistics

• Engaged students in one-on-one consultations designed to supplement and reinforce material

• Lead group-based study, helping students to achieve deeper understanding of curriculum and to develop versatile problem solving techniques

• Communicated difficult concepts in creative ways personalized for the individual based on their learning styles, fostering academic growth and efficient study skills

• Worked closely with professors in classroom workshops to facilitate student learning and provide constructive feedback to aid in lesson planning Department Lead

BARNES & NOBLE, Costa Mesa, California 2009 – 2015

• Proactively cross-trained in all aspects of store operation, including: sales, customer service and technical support, food service, logistics

• Analyzed customer purchase patterns to drive sales, resulting in departmental sales increase of 9% year-over-year

RECENT PROJECTS

Authorship Attribution Summer 2016 – Current

• Research assistant, conducting text analysis with University of Alberta faculty in Literature and Statistics, employing statistical and machine learning techniques such as support vector machines, classification, and cluster analysis

Animal Shelter Outcome Prediction Spring 2016

• Assumed leadership role, establishing a project outline, implementing a collaboration and documentation scheme, monitoring progress, and synthesizing results

• Methods included random forests, boosting, k means clustering UCLA DataFest April 2016

• Competed with a four-person team on Ticketmaster customer data set, cleaning and summarizing the data and building a classifier model based on inherent and engineered features with the goal of distinguishing true fans from scalpers SKILLS

Programs: Adept in R, Excel and Word, Google Docs and Sheets. Familiarity with SAS, Stata, SPSS Operating Systems: Proficient with PC and Mac

Languages: Fluent in Spanish

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