About

About

Introduction

Hi, I’m Alex, a highly motivated and results-oriented Data Scientist/Data Analyst with a passion for turning data into actionable insights. I enjoy tackling complex problems and developing creative solutions using a combination of technical skills and analytical thinking. My background in computer science and data science, combined with my enthusiasm for sports analytics, allows me to approach challenges from a unique perspective.

Skills

I possess a diverse range of skills essential for effective data analysis and problem-solving:

  • Data Visualisation: Creating clear and impactful visuals to communicate data insights.
    • Tableau: Building interactive dashboards and reports to explore and present data.
    • Python (Matplotlib): Generating custom visualisations and plots for detailed analysis.
    • Information Visualisation Principles: Applying best practices to design effective and engaging visualisations and dashboards.
  • Data Analysis & Manipulation: Extracting, cleaning, and transforming data to uncover meaningful patterns.
    • Python (Pandas, NumPy): Performing data manipulation, cleaning, and analysis.
    • Alteryx: Automating data preparation and blending workflows.
    • Statistical Analysis: Applying statistical methods to analyse data and draw conclusions.
  • Machine Learning and AI: Building predictive models and algorithms to extract insights and make predictions.
    • Python (Scikit-learn): Implementing various machine learning algorithms for classification, regression, and clustering tasks.
    • Model Evaluation & Selection: Assessing model performance and choosing the best model for a given problem.
  • Statistical Modeling: Building mathematical models to represent and analyse real-world phenomena.
    • Python (PuLP): Implementing optimisation models for decision-making.
    • Monte-Carlo Simulation: Performing simulations to analyse risk and uncertainty.
  • Database Management: Working with relational databases to store, retrieve, and manage data.
    • SQL: Querying and manipulating data in relational database systems.
    • MS SQL Server: Experience with Microsoft SQL Server database management system.
    • Azure SQL DB, Firebase (Firestore) & DB AWS Dynamo DB: Familiarity with cloud-based database services.
  • Cloud Computing: Utilising cloud platforms for data storage, processing, and analysis.
    • Azure: Experience with Microsoft Azure cloud services, including Functions and SQL Database.
    • GCP: Familiarity with Google Cloud Platform, including Cloud Functions and Cloud Deploy.
    • AWS: Basic knowledge of Amazon Web Services, including Lambda functions.
  • Front-End Development: Proficient in building interactive and responsive user interfaces using modern web technologies.
    • HTML, CSS, and JavaScript: Solid foundation in core web development languages.
    • React: Experience with building dynamic and reusable UI components using the React framework.
    • Tailwind CSS: Utilizing Tailwind CSS for efficient and customizable styling.
    • Framer Motion: Implementing animations and transitions for enhanced user experience.
  • Back-End Development: Developing and maintaining server-side logic and APIs for web applications.
    • Python (Flask): Building RESTful API web services using the Flask framework.
    • Firebase Authentication and Databases: Integrating Firebase for user authentication and data management.

Academic Experience

University

BSC Computer Science (Digital & Technology Solutions) - 2:1

Digital & Technology Solutions Professional (Data Analyst Pathway) - Level 6 Apprenticeship

During my studies, I developed a strong foundation in data visualisation, data analysis, machine learning, and cloud computing. I further enhanced my skills by completing a Masters Level module in Data Science, achieving a 1st class grade.

My passion for sports analytics led me to write my dissertation on “Machine Learning Models for Probabilistic Football Analysis and Prediction,” which also received a 1st class grade. This project allowed me to apply my data science and machine learning knowledge to a real-world challenge, developing predictive models to analyse and forecast football outcomes, as well as developing my own custom expected goals (xG) model.

Sixth Form

International Baccalaureate Diploma Programme

  • Awarded 43/45 points (equivalent to A* A* A* at A-Level)
    • Higher Level (HL):
      • Computer Science (Level 7 - equivalent to A*)
      • Economics (Level 7 - equivalent to A*)
      • English (Level 7 - equivalent to A*)
    • Standard Level (SL):
      • Latin (Level 7 - equivalent to A*)
      • Mathematics (Level 6 - equivalent to A)
      • Classics (Level 6 - equivalent to A)
    • Core Points: 3/3 (Extended Essay and Theory of Knowledge)

Secondary School

GCSEs

  • Awarded 7x Level 9, 2x Level 8, 1x Level 7, 1x A
    • Level 9 (equivalent to A**):
      • Computer Science
      • English Literature
      • Geography
      • History
      • Biology
      • Chemistry
      • Physics
    • Level 8 (equivalent to A*):
      • Mathematics
      • Latin
    • Level 7 (equivalent to A):
      • English Language
    • Grade A:
      • Japanese

Professional Experience

Over the past 4 years, I have gained valuable professional experience at one of the Big 4 professional services firms, working in a range of areas in the Data & Analytics practice.

Across this time, I have honed my skills in data visualisation (Tableau), database management (SQL), as well as interpesonal presentation and communication skills. This has been achieved through various projects, including development of interactive client dashboards, implementation of complex SQL rule logic, and effective communication of technical data-insights to diverse audiences. More recently, I have focused on automating internal tracking processes using Python. I developed and deployed data management solutions that streamlined workflows and significantly reduced manual effort, saving the company valuable time and resources.

Personal Interests

Outside of work, I am a big sports fan. I enjoy playing Football (and most other sports in general), as well as supporting Liverpool FC and taking a keen interest in Formula 1 and Darts. I also have a mild obsession with Fantasy Premier League. In the 2022/23 season, I pursued a data-informed approach to optimising FPL team selection, achieving an overall rank of 1,326 out of over 10 million players. Additionally, in this season, I won 20 consecutive head-to-head ties to win the Liverpool cup competition. I have unfortunately accepted that my FPL career is only going downhill from that season.

I also enjoy applying my data analysis skills to personal sports analytics projects. I’ve developed statistical models and analyses in all of the afformentioned sporting endeavours, exploring different data science and machine learning techniques. You can find a selection of preliminary write-ups for these on this site, with plenty more in the pipeleine (when the time allows!).