Ahmed Gurbuz

I am a problem-solver and creative Data Analyst professional with experience in both the private and government sector.

I translate data into valuable and comprehensible insights. My goal is to improve results with data-driven facts and help decision-makers. I interacted with many internal and external teams including executive level management teams and ambassadors. I demonstrated significant leadership qualities as well as the ability to work independently and as a team member. I am a quick learner with strong analytical and statistical skills.

I have been working as a Data Analyst in HazMat Training Department at International Association of Fire Fighters (IAFF) in Washington, DC since July 2021.

I have a background in the following sectors: Public Safety, Insurance, E-Commerce, International Relations, and Energy. I have 2+ years of work experience as an E-Commerce Data Analyst from two different start-up companies in Dallas, TX and 5 years of work experience as a Political Analyst (Foreign Service Career Officer/Diplomat) at Turkish Ministry of Foreign Affairs. I hold Master of Economics (ME) Degree from North Carolina State University in Raleigh, NC, a Certificate on Data Science from Southern Methodist University in Dallas, TX, and Bachelor of Arts (BA) Degree in Economics from Fatih University in Istanbul, Turkey.

I am bilingual, fluent in English and Turkish. I lived in 5 different countries and visited 11 different countries.

Technical Skills

My Portfolio Projects

Coronavirus Disease (COVID-19) Dashboard

Dashboard for coronavirus disease (COVID-19) outbreak statistics in the world using Tableau. Dashboard is connected to live data source of the official Tableau COVID-19 Google Sheet and could be updated real-time.

Baseball Statistics

This is a full-stack web application including three user interactive data visualizations of baseball statistics using "Sean Lahman's Baseball Database" from SQLite Database.

Visualizing Locations of PetPals

This is a full-stack web application project allowing users to enter information about their pets then renders a chart visualizing the location of their pets depending on the information submitted by the user.

Visualizing Earthquakes in Last 7 Days

In this project, the earthquakes occurred in the last 7 days around the globe is visualized using the United States Geological Survey (USGS) GeoJSON data

UFO Sightings

An interactive webpage displaying a table of UFO sightings and allowing users to filter the data through an HTML form created with JavaScript and D3.js

Mission to Mars

Websites including image and text data related to Mars are scraped with Beautiful Soup (BS4) and then collected data is loaded to MongoDB database through Python and displayed on a HTML page using Flask app

Analyzing Drug Treatment

In this study, 250 mice were treated through a variety of drug regimes over the course of 45 days. Their physiological responses were then monitored over the course of that time. The objective is to analyze the data to show how four treatments (Capomulin, Infubinol, Ketapril, and Placebo) compare.

Bacteria Biodiversity Dashboard

An interactive dashboard to explore the Bacteria Biodiversity dataset.

Weather Analysis Dashboard

This project analyzes the weather of randomly selected 571 cities across the world of varying distance from the equator. The objective is to observe whether the distance of the city from equator has an effect on temperature, humidity, cloudiness and wind speed or not.

Employees Database

In this project, the database of employees at the Pewlett Hackard corporation from 1980s and 1990s is analyzed. Tables are designed to hold data in the CSV and then those CSVs are imported into a SQL database. Data Modeling, Data Engineering, and Data Analysis skills are performed to derive results.

Purchasing Data Analysis of an Online Game

In this study, I analyzed the purchasing data of Heroes of Pymoli to draw meaningful insights. Heroes of Pymoli is a fantasy game of which is free-to-play, but players are encouraged to purchase optional items that would enhance their playing experience.

Bike Count Prediction

A machine learning project that predicts the number of bikes count using Boosted Decision Tree Regression model
on Azure ML Studio

•        Full Portfolio

My Certificates from MOOCS