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Michael Kung

Senior Data Analyst

About Me

Michael Kung is a motivated, self-starting Data Analyst with a can-do attitude and thrives under-pressure. Passionate about data, presenting data, and utilizing data to drive business decision. Known among co-workers and team members for stellar problem-solving and communication on large-scale projects. Seeking to leverage data analytical skills to improve corporate performance.

Michael codes primarily in Python and SQL but also proficient in languages: JavaScript, HTML+CSS, R. Adept in Machine Learning (Scikit-Learn, Keras, PySpark), Statistics, and Exploratory Data Analysis. Experienced in using various tools for data engineering data analysis, and reporting (Tableau, Alteryx, SQL, Python, R).

Contact Me:
Email: m.kung889@gmail.com
LinkedIn
GitHub

Experience

Whole Foods Market

Senior Data Analyst

  • Piloted space discover initiative to expand insight into store space where company was once blind to.
  • Designed data model and engineered foundational Macro Space data and automated ETL into date warehouse.
  • Led the development and enhancements of foundational Macro Space data and reporting.
  • Subject matter expert of company’s space data. Hosted trainings to empower partners in utilizing foundational data and reports.
  • Collaborate with cross-functional teams of data science and business teams to gather business/functional requirements and create novel evergreen process to proactively optimize category space in stores.
  • Used python to create optimization function to give space change recommendations optimizing for sales.
  • Performed post-measurement analysis in various initiative/events and presented results, insights, and recommendations to leadership.
  • Design, engineer, and maintain automated data ETL pipelines to source and aggregate required data for various data analyses and reporting needs.
  • Serve as an analytical and technical thought-partner to stakeholder teams, helping to develop actionable insight out of complex analytics.
  • Create self-serve tools using advanced excel macros and Tableau dashboards to enable and ensure global merchandising strategy are successfully executed.

Data Analyst

  • Data engineering from multiple databases (PostgreSQL and Teradata) for reporting, data analysis, and modeling.
  • Develop and maintain Tableau reports/dashboards/visualizations to drive data driven business decisions.
  • Perform ETL and data analysis with various tools (Alteryx, Python, SQL, etc.).
  • Predictive modeling in R and Python: Created space to sales elasticity model.
  • Provide ad hoc data reporting and engineering solutions.

Data Analyst (Contractor)

  • Created advanced custom SQL queries in multiple databases to create Tableau data sources for reporting.
  • Created 20+ tableau reports/dashboards and published to Tableau Server to validate floor plans and flag any floor plan errors, saving Floorplanning partners hours of manual floorplan validation.

Fidelity Dental P.A.

System Administrator + Office Manager

  • Spearhead new patient acquisitions. Increased number of monthly new patients by 200% through data analysis and marketing strategies.
  • Develop and structure a MySQL database to collect and analyze practice data such as production/collection of each dentist and patient demographics
  • Generate data visualizations to report practice performance, financial analysis and profit/loss reporting.
  • Install/maintain/configure practice management software and computers.

Univeristy of Texas at Dallas

Graduate Researcher

Studied the effects of aging has on memory.

  • Performed experiments and analyzed data researching aging memory.
  • Utilized SPSS to run statistical analysis to analyze the relationship between neurochemistry and behavioral data.
  • Conducted and created visualizations for data presentations and data analysis using advanced excel.

Education

Machine Learning by Stanford University on Coursera

Issue Date: June 2019

Machine Learning Course Certification

Credential ID: HSQDYHPE4W6J

University of Texas at Austin McCombs - Red McCombs School of Business

Oct 2018 - April 2019

Data Analysis and Visualization Certficiate

University of Texas at Dallas

Aug 2015 - May 2017

Master of Science in Applied Cognition and Neuroscience

Texas A&M Univeristy

Aug 2010 - May 2014

Bachelor of Arts in Biology w/ Minor in Business

Projects

Medical Insurance Charge Regression Modeling

In this notebook, we will explore several types of Regression models on a Medical Cost dataset found on Kaggle( https://www.kaggle.com/mirichoi0218/insurance ) to see if we can predict if certain factors can predict medical costs. This data set shows individual medical costs as billed by insurance. The identity of each individual is hidden but some personal data is given such as: age, sex, BMI, how many children they have, if they are as smoker, and what region they are from. We have no data on the diagnosis of patients. But we have other information that can help us to make a conclusion about the health of patients and practice regression analysis.

View Project

Movie Recommender App

This app recommends movies using Matrix Factorization machine learning. The Matrix Factorization model will find similarity between movies (based on how they are rated by users) and user similarity (based on how similary users rate the same movie). The model then uses these similarities to predict how a user may rate movies. A python script is written to grab each user's top 5 recommneded movies. A Flask app is used to display the top 5 recommended movies for the selected user id. An api is used to grab information on each of the recommended movies.

View Project

Belly Button Diversity Dashboard

An interactive dashboard visualizing belly button diversity data from Rob Dunn Lab (http://robdunnlab.com/projects/belly-button-biodiversity/). This is a Flask app that accesses belly button data stored in an sqlite file. JavaScript is used to populate the dropdown options so user can select which sample ID to visualize. Plotly.js is used to create pie and bubble chart.

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Earthquake Map

An interactive app that shows where earchquakes have occured. Each marker varies in radius and color, depending on earthquakes' magnitude. When a marker is clicked, a popup appears showing additional information about the earthquake. (Data source: http://earthquake.usgs.gov/earthquakes/feed/v1.0/geojson.php) This project uses: Leaflet, JavaScript, geoJson, HTML, CSS

View Project

Skills