Student Data Analyst
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I am a proactive and reliable fresh graduate Math and Stats student at MacEwan University (June 01, 2023) with hopes of kickstarting my career as a data analyst.Over the course of my studies, I have developed a passion for data analyzing, machine learning and a love for collaboration. I am always eager to learn and adapt to new environments. As I further my experience, I hope to gain more professional experience and knowledge within the industry.
September 2022-Current
Edmonton, Alberta, Canada
Analyzed, explored, and inspected data set for research
Prepared and presented narratives and explanations to accompany statistical data.
Filtered and “cleaned” data by reviewing computer reports, printouts, and performance indicators. Interacted with management to prioritize the most important needs.
September 2022-April 2023
Edmonton, Alberta, Canada
Adapted during hectic hours and developed priority tasks to meet deadlines. Motivated students to accomplish assignments.
Aided the needs of existing and new students and efficiently manage them.
September 2021-August 2022
Edmonton, Alberta, Canada
Reinforced a rubric system to fairly judge students' assignments
Utilized critical thinking to recognizing alternate formats/ solutions that are correct. Flag students work as necessary following pre-determined criteria
June 2018-August 2022
7-ELEVEN INC.
Edmonton, Alberta, Canada
Analyzed and carefully finished daily work shift reports to be submitted to 7 Eleven accounting office.
Planned and forecasted items to be ordered basing from last week's activity of sales. Managed employees during a working shift by communicating clearly and listening actively.
2019-2023
BACHELOR OF SCIENCE DOUBLE MAJOR IN MATHEMATICS AND APPLIED STATISTICS
Edmonton, Alberta, Canada
GGPA: 3.645
Worked with a client to identify scope of work for analyses, dashboards, and reports. Planned an agenda to be discussed once in every two weeks.
Applied Time Series Analysis (Community Partner Project)
Analyze the biweekly engagement of one of King Business Solutions’ customer with time series and finding out a model (seasonal and non-seasonal) to interpret the trend.
Used classification and machine learning methods to predict whether an individual will accept a marketing offer.
Studied the relationship between leisure hours and categorical variables (demographics), then finding the best model and testing its accuracy.
Model the relationship between leisure hours and predictor variables which consists of categorical and numerical variables then finding the best model for prediction.
