Experience

Attraction Tickets Ltd

• United Kingdom
• Travel Arrangements
• 1 - 100 Employee

• Trainee Data Analyst

  • Mar 2023 - Present



General Assembly

• United States
• Higher Education
• 700 & Above Employee

• Data Science Student

  • Nov 2021 - Feb 2022

  A full-time 12 week long course designed to cover the key aspects of data science from collecting and cleaning data to modelling and presenting findings using Python. The course also contained several individual projects culminating in a capstone. The capstone project was spread over six weeks and involved me using APIs to gather data on TCGs (trading card games) in order to build a model that predicted the prices of trading cards. The features utilised from the dataset covered a wide variety of data types and required a number of different solutions such as NLP, while the target data also posed an interesting challenge due to its non-normal distribution. Particularly interesting tools that were used in the project include Tweedie regression models and specific RegEx strings for different text data. The results obtained did manage to outperform the baseline by a significant margin (albeit the baseline is very low for this problem) and the project overall gave me valuable experience in dealing with complex datasets while still leaving room for further inquiry. Other notable projects during the course involved classifying the salaries of job listings on indeed.com as high or low and predicting house prices using the Ames Housing dataset. The former required a lot of web scraping and the latter careful handling of missing values in the dataset. NB all these projects can be found on my github