Thomas J Cartwright

Chief Technology Officer and Cofounder

• Contributed to strategic vision and development of innovative AI solutions.
• Engaged with investors and partners to secure funding and drive growth.
• Oversaw R&D, aligning projects with goals.

Machine Learning Engineer

Machine Learning Engineer

• Developed and productionised a deep learning NLP model to perform fuzzy matching on a noisy text dataset using Python, Tensorflow and AWS. This model improved the quality and accuracy of search results presented to the user.
• Designed, implemented and productionised a ranking model, using LightGBM, to improve the efficiency of data collection. This model was trained on a large, noisy dataset and improved data quality whilst reducing data collection costs.
• Maintained and monitored production machine learning software hosted on AWS (S3, Sagemaker, Athena)
• Designed, implemented and productionised a survival model to optimise data retention using python, pandas and numpy which reduced the cost of unnecessary data collection.
• Performed exploratory analysis on large, noisy datasets using Pandas, Numpy and AWS (SageMaker, Athena, Glue and S3)
• Present data analysis and machine learning solutions to non technical members of staff

MSc Dissertation

• Developed an unsupervised clustering and user recommendation system to increase engagement and quality of user task completion.
• Implemented deep autoencoders using Keras and Tensorflow.
• Developed hybrid recommender systems using Word2Vec and SpaCy

Software Developer

• Developed an online app using Python (Numpy, Scipy), C# .NET, Javascript, React and SQL
• Led the design and implementation of a microservice that matched large volumes of incoming messages to complex queries using Python, Scipy and Linear Algebra
• Participated in the design and implementation of a component that clustered large volumes of incoming messages
• Worked in a team to implement data analytics software that allowed users to visualise and analyse social media interaction data. This allowed clients to gain actionable insights from large volumes of unorganised data.
• Developed integrations with a large number of social media APIs, ensuring minimal data was collected to keep operational costs low and ensure clients only saw relevant information.
• Presented and described technically complex components to technical and nontechnical members of the team

QA Lead and Software Developer

• Developed an online app using C# .NET, Javascript, SQL, HTML and Python
• Initiated and led the entire testing process leading to fewer bugs, a more robust product and a faster development cycle
• Developed a system to automate 90% of testing using C# and Selenium.
• Responsible for release date decisions. This involved balancing customer requirements with product quality and bug risk.
• Gathered feedback from clients to align future product development with client needs.
• Communicated and demonstrated the product to technical and non-technical stakeholders

University of Edinburgh

• Machine learning (ML): models developed in Python, using numpy, scipy, sklearn, matplotlib, seaborn and pandas
• Reinforcement learning: researched and trained robotic simulations using Tensorflow and Keras
• Deep neural networks: developed image classification models and recommender systems
• MSc dissertation: developed a recommender system for the citizen science portal SciStarter
• Development of unsupervised clustering and user recommendation systems to increase engagement and quality of user task completion.
• Implemented deep autoencoders using Keras, Tensorflow and Word2Vec
• Research and presented a literature review on music genre classification using convolutional neural networks
• Created FinTech proposal to harness banking data via ML
• Participated in “3-day startup” team to quickly develop real-world ideas into prototypes
• Demonstrated effective time management by studying part time alongside full time employment
• Completed literature review on Music Genre Classification using Convolutional Neural Networks

University of Edinburgh

• Focused on topics such as statistics, probability, group theory, linear algebra and graph theory.
• Researched and presented a paper on the Mathematics of Music. This involved developing a system to generated music through mathematical group theory.
• Developed digital signal processing techniques with fourier analysis in MATLAB
• Selected for the year abroad program, where I studied at the University of Miami in my third year