Security Officer Prevention

Tyrrance Pernell Miller Jr.

Charlotte, NC 980-***-**** ***********@*****.***

Data Analytics

Experience in data acquisition, data modeling, and statistical analysis. With a background in data analytics, I bring strong skills in data preparation, and SQL databases to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. My goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.

TECHNICAL SKILLS

Python, Data visualization, SQL, scikit-learn, NumPy, Pandas, Data Aggregation, Tableau, JSON, Seaborn, HTML, CSS, Relational Database

TECHNICAL PROJECTS

“Ames Housing Sale Price Analysis”

AMES-Housing-Price-Analysis

For this project, I used descriptive statistics and data visualization to produce a report about the home sales in Ames, Iowa between 2006 and 2010.

● Created visualizations using python to plot the difference between subsets as well as interpreting the plots.

● Utilized Pandas library to display properties of dataframes (number of rows/columns, column names, presence of missing data, etc.)

● Performed Data splitting to separate the data based on the condition of the homes to determine the price between the subsets.

● Used code to engineer a new feature based on the values in the dataset.

“Microsoft Movie Recommendations”

Microsoft-Movie-Studio-Analysis-

For this project I used exploratory data analysis to generate insight on movie studios and types of films that are doing well at the box office for Microsoft stakeholders. I then translated those findings into actionable insights that the head of Microsoft's new movie studio can use to help decide what type of films to create.

● Performed Data preparation that is reproducible,justifiable, and well documented using (Pandas, Matplotlib)

● Performed Data Manipulation and Analysis with Pandas to answer business questions in a relatable and performant way.

● Gathered Data and Created Data visualizations to display the movie studios with the Highest Domestic Gross,Release Dates with the highest profits, and Average Rating of Movie Genres using SQLite3, and Pandas.

● Performed Data Communication

“Health Survey Data Analysis”

Health-Survey-Data-Analysis

In this project I performed statistical data analysis on a dataset from the Center for Disease Control and Prevention

(CDC). Specifically focused on the relationship of the physical health (PHYS HLTH) of people who rent their home and those who own their homes (RENTHOM1).

● Prepared data by converting all instances of 88 to 0, and dropped all of the records where (PHYS HLTH) is 77, 99, or blank (NaN) by only pulling data for all values between 0 and 30.

● For (RENTHOM1) I dropped the records with values other than 1 or 2.

1: Those who owned their homes.

2: Those who rent their homes.

● Calculated the confidence interval for the mean of physical Health

● Performed t-testing to find the difference in physical health based on whether someone rents or owns their home and to if it is statistically significant.

● Performed data splitting to separate the records based on the value of RENTHOM1 (i.e. whether the person owns or rents their home).

“King’s County Housing Regression Modeling Project” Data-Modeling-Project

The dataset that is being used for this project is from the King's County Housing portal, which contains roughly over 30,000 rows of data for 2021-2022 home sales in King County, Washington. I will be using this data to create statistical models that will help determine the best features and how they relate to price (Regression Target). I first started by preparing my data by pulling the dataset and overviewing the columns and rows to see what features would be best to use and then took out the outliers in the data set. I then created my baseline models and iterations of the models to eventually get to my final model and the two best features. EMPLOYMENT HISTORY

Warehouse Associate, Amazon, Charlotte, NC 04/2020 - Present

● Fulfill the logistics behind receiving, processing and storing inventory according to purchase orders and store policy.

Loss Prevention Officer, Old Navy, Charlotte, NC

05/2019 - 03/2020

● Employed a number of tactics to reduce the amount of theft in stores. Covertly monitor suspicious individuals by posing as shoppers or monitoring video feeds in a control room. Security Officer, Hilton Charlotte University, Charlotte, NC 06/2012 - 05/2019

● Observed and reported disturbances in the hotel/ around the premises of the hotel EDUCATION

Flatiron School, New York, NY 02/2022 - 10/2022

Immersive Data Analytics Bootcamp program, October 2022

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