↳ ABOUT

Turning data into actionable insight

I'm a Senior Data Scientist with a passion for engineering and problem-solving. I thrive on learning new skills as the challenge at hand demands them. I'm driven to get solutions out there and in front of the right people.

With expertise spanning machine learning, edge-deployed AI, acoustics, and digital signal processing, I've tackled a great many number of unique challenges in the data space. From extracting insights from massive enterprise data lakes to deploying advanced ML systems in harsh operational environments at the edge; I've got experience tackling data science problems of many shapes and sizes. Ultimately; the end goal is still the same - I help people transform data into confident decisions and action.

My journey began like many with a degree in physics, driven by a passion for explaining our complex world through the language of mathematics. That curiosity has driven my work in data ever since.

↳ LOCATION

Based in London

↳ EXPERIENCE

Work History

Mar 2024 - PRESENT

Senior Data Scientist

Daintta

At Daintta, I serve as a subject matter expert in ML Engineering, large-scale system design, digital signal processing, and underwater acoustic systems. I currently specialise in building scalable edge-capable AI. Within this role, I also led national-level forecasting and demand analysis for strategic resource planning in emergency services.

Jan 2023 - Mar 2024

Data Scientist

Convera

In this role, I was largely responsible for the development of revenue forecasting and churn prediction models, leveraging a variety of large-scale b2b transactional datasets. At Convera, I deployed and maintained ML pipelines on AWS SageMaker and Snowflake, and optimised executive dashboards for real-time business monitoring and decision-making.

Aug 2021 - Jan 2023

Data Scientist

Sky

While at Sky, I built real-time Kafka streaming pipelines for network telemetry and health metrics for the effective monitoring of distributed smart devices (SkyGlass). Here, I also analysed new device rollout data to identify critical issues for engineering teams, developed performance dashboards, and optimised ETL processes in Airflow.

↳ TECH STACK

Machine Learning

PyTorchTensorFlowScikit-learnHugging FaceMLflow

Data Engineering

PythonSQLSparkPandasNumPy

Cloud & DevOps

AWSDockerKubernetesGitCI/CD

Visualization

TableauPlotlyMatplotlibSeaborn

↳ EDUCATION

MSc Data Science

2021 - 2022

Queen Mary University of London

BSc (Hons) Physics

2015 - 2019

University of Glasgow