Adrian Warner

Background

About Adrian Warner

Over a decade of experience practicing Lawful Interception, Software Engineering and Data Science on large volumes of data at high speeds, having a unique understanding of working with Law Enforcement and the wider international Intelligence Community. Such work involved reverse engineering of communication protocols, developing and deploying event-driven processing systems on a global scale, designing event signatures and applying streaming analytics & Machine Learning across high volume event stream outputs.Having experience of implementing ML processing pipelines on Public and Private Cloud in Python, either via Apache Spark or Serverless Functions, Apache Airflow & BigQuery. Utilising such tools as JupyterLab, Plotly/Dash and D3 to perform exploratory data analysis, mostly with unsupervised learning techniques, for the purpose of identifying patterns and use cases in data. Possessing a comprehensive understanding of Deep Learning from first principles, utilising libraries such as NumPy through to Keras/Tensorflow2. Inherently competent in Feature Engineering, Data Acquisition, ETL, Streaming and bulk storage NoSQL techniques.Thorough practical experience in implementing Deep Learning Libraries for Natural Language Processing, specifically SpaCy and it’s annotation tool Prodigy. This includes implementation within a distributed web crawler, for large scale document classification and named entity recognition. Along with the design and implementation of a suitable knowledge graph within Elasticsearch and an appropriate GraphQL interface with which to query it, from mobile clients written in React Native.Fully literate in Cloud technologies and CI/CD techniques, having developed applications with Git, TeamCity, Docker, Kubernetes and Cloud Functions/Lambda via Infrastructure as Code (Terraform/Ansible). Such tools allow for the pioneering delivery of an Agile Data Science platform and process, facilitating rapid prototyping and development, to prove theory and deliver improvements seamlessly. Diligent self learner and researcher, who enjoys reading new technical content, either via online learning resources, research papers or prominent topical blogs.