Data Analyst

KAITLYNN GABRIEL

***************@*****.*** 916-***-**** www.linkedin.com/in/kaitlynn-gabriel

SUMMARY

Applied Mathematics student with a strong interest in supporting teams with developing and maintaining data analytics solutions. Certified Microsoft Transact-SQL data analyst. Enjoys learning new concepts and working in a team-based environment. TECHNICAL SKILLS: Python, Java, JavaScript, R, T-SQL, MATLAB, MS Excel, GitHub, Jupyter Notebook, Highcharts, D3, HTML, CSS, Probability, Statistics, Multivariable Calculus, Linear Algebra EDUCATION

Bachelor of Science (B.S.) in Applied Mathematics Minor Data Science UNIVERSITY OF CALIFORNIA, SAN DIEGO

Anticipated Completion: June 2021

PROFESSIONAL CERTIFICATIONS: DAT201x: Querying Data with Transact-SQL Certification Microsoft September 2020 RELEVANT EXPERIENCE & COURSEWORK

MICROSOFT CERTIFICATION: QUERYING DATA WITH TRANSACT-SQL September 2020 Skilled with Transact-SQL to develop and support data analytics solutions.

· Filter, sort, join, aggregate, and modify data

· Use sub queries, table expressions, grouping sets, and pivoting

· Create views, user-defined functions, and stored procedures

· Implement error handling, transactions, data types, and nulls INTRO TO DATA VISUALIZATION Fall 2020

Designed an HTML website analyzing the influence of a sports manga on the 237% increase in participation in Japanese volleyball.

· Undertook a user-centered design approach by incorporating interactive charts to simplify my findings. Programmed a dashboard to evaluate the sales performance and stock prices of a company selling knives and forks. THE PRACTICE AND APPLICATION OF DATA SCIENCE Spring 2020 Created a linear regression model using Python to predict how much money an organization spent on a Snapchat political ad.

· Implemented features such as one-hot encoding to improve the baseline model. This new feature enabled easier category encoding for the machine learning process and allow the model to provide better predictive results.

· Through analysis and testing of several models, increased accuracy of predictive model from 76% to 80%. EXPLORATORY DATA ANALYSIS AND INFERENCE Spring 2020 Delivered an improved classification model in R that reduced the error rate by 5% to predict if an email was spam.

· Collaborated in a team of 3 students to develop a model through assessment of data transformations, analysis methods, and classification models.

DATA STRUCTURES AND ALGORITHMS FOR DATA SCIENCE Winter 2020 Implemented common data structures and sorting algorithms in Java to design resource efficiencies including throughput times and storage limits.

· Implemented a queuing algorithm that efficiently assigned fitting rooms to customers with less than 10-minutes of wait time.

· Programmed a movie search engine using a binary search tree and evaluated different tree traversals methods to collect data.

· Utilized Huffman coding tree method to provide lossless data compression for large text files that minimize storage allocation requirements.

PROGRAMMING AND BASIC DATA STRUCTURES FOR DATA SCIENCE Spring 2019 Developed applications that implemented key techniques of abstraction and object-oriented programming in Python. Designed and developed a tower defense game of Ants vs Bees.

· Used class constructors to define characters’ health, armor, and actions. Developed a Yelp restaurant recommendation program.

· Used applied k-means clustering analysis to identify the restaurant with the shortest distance from the user’s location.

· Used least-squares linear regression analysis to predict how a user would rate restaurants. PROFESSIONAL INVOLVEMENT

UCSD WOMEN IN BUSINESS Fall 2019-Present

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