kyle swire-thompson

After gaining valuable experience in the field of data analytics and Python development, I welcome an opportunity that aligns more closely with my academic background and passion for leveraging data for insights. Both my bachelor's and master's dissertations revolved around the exploration and application of Python-based data analytics tools and techniques particularly with the use of machine learning, highlighting my keen interest in this field. I aim to further develop my expertise, contribute to innovative projects, and make a meaningful impact in harnessing data-driven solutions. My proficiency in Python, AWS services (such as CloudWatch, and S3), data manipulation with SQL, GIT for version control, and various data analytics libraries equips me for this transition. Additionally, my experience with machine learning frameworks like PyTorch and TensorFlow, as well as my knowledge of Elasticsearch, positions me well for a Python developer or data analytics role. I am seeking a challenging position to apply my Python development skills and data analytics expertise, leveraging my background in data analytics to innovate and contribute to impactful projects in the field of data analysis and data-driven decision-making.

WORK EXPERIENCE 

OCTOBER 2021 – OCTOBER 2023 

SOFTWARE DEVELOPER, CENSORNET 

As a Software Developer in the Data Analytics Department at Censornet, I've enhanced data analytics and cybersecurity efforts. I developed efficient Elasticsearch query solutions, developed, and maintained a Flask-based OpenSearch endpoint to handle production data queries from a UI, and produced efficient SQL solutions. I also Leveraged AWS services, enhancing scalability and security. Additionally, I built a serverless CloudWatch dashboard for real-time insights into logs. These contributions have significantly boosted departmental efficiency and cybersecurity capabilities. 

AUGUST 2021 – OCTOBER 2021 

MACHINE LEARNING ENGINEER, CENSORNET 

During my first contract at Censornet, I served as a Machine Learning Engineer and successfully designed and developed a Malicious URL Machine Learning detection application. I meticulously analysed and processed large datasets to identify patterns in malicious URLs. I consistently reviewed and improved the codebase, ensuring its optimal performance, and diligently verified that inputs and outputs matched example code, maintaining a high standard of reliability and consistency in this critical cybersecurity project. 

MAY 2021 – AUGUST 2021 

RESEARCH ASSISTANT (SUMMER PLACEMENT), CARDIFF UNIVERSITY 

As a Research Assistant at Cardiff University, I played a vital role in the development of a Cyber-Risks Assessment and Threat Modelling Based Energy Load Forecasting Methodology and Tools. I created a Python-based machine learning tool for energy load forecasting and designed an AI cyber event detection system for industrial control systems. These projects advanced our understanding of cybersecurity and situational awareness in critical infrastructure sectors. This work was also published.

EDUCATION 

2021 – 2022 

MSC CYBER SECURITY AND TECHNOLOGY, CARDIFF UNIVERSITY 

Received a full scholarship for this degree based on performance. 

Achieved a merit grade. • Dissertation on the use of generative adversary networks (GANS) to aid in training metamorphic-type malware ML detection models. 2018 - 2021 BSC COMPUTER SCIENCE, CARDIFF UNIVERSITY 

Graduated with First Class Honours. 

Dissertation: “Cyber Event Detection and Machine Learning Classification for Situational Awareness in Industrial Control Systems.” Developed and deployed a predictive model framework using Python and WEKA.