CV and Portfolio
Hi! My name is Curtis Hunter and I am a Data Scientist currently working for the UK Civil Service, based in Bristol.
Working on Stata projects during my formal education at Warwick in Economics introduced me to the world of Programming and Econometrics. I subsequently transitioned from a Data Analyst role at TESLA Inc. into my current Data Scientist role where I've have dedicated myself to continuous learning and embraced a relentless pursuit of knowledge in the field!
I have extensive experience in data analysis, machine learning, data visualisation and managing ETL pipelines using SQL Server, R and Python.
This has involved gaining a proficiency in libraries such as Scikit-learn, Pandas, Tensorflow, RShiny, Tidyverse, Networkx and NumPy.
I am also skilled with data science tools such as MS Power Platform (PowerBI, PowerApps etc.), AWS, Azure, Git, Excel (Microsoft Certified), Docker and many more.
Regrettably, I cannot show any of my professional porfolio for confidentiality reasons. However, I've curated a selection of personal projects below which I have completed just for fun!
Using a Stanford Network Analysis Platform dataset, I have created a LightGBM model which predicts the country that LastFM users are from. I've also made an accompanying dashboard where you can interactively explore the data and use the deployed model (on AWS) to make a prediction.
Have you ever heard of the Bacon Number? If not, the concept is as follows: an actor who was in a movie with Kevin Bacon has a Bacon Number of 1. An actor who was in a movie with someone that has a Bacon Number of 1, has a Bacon Number of 2. This continues indefinitely.
Using data that I collected from the TMDB API (over 10 very long hours), I have created 'the Bacon Number' but for composers who have worked with Hans Zimmer!
Watch as World War 2 unfolds, with an animated visualisation of the bombing locations over the course of the war along with key events being noted on the map.
I collected the data from 2 separate data sources and combined them to produce hundreds of separate plots which I then transformed into 3 animated geospatial visualisations.
Using Numpy and Matplotlib, I've built a few popular machine learning models from scratch. I've provided comments and markdown to explain and show interesting plots about what is happening on each step of the model building process.
This is a notebook for a Kaggle competition that I entered recently. I had a lot of fun working with neural networks in this project and learning about how the dataset worked.