About Fathom Data

Matt holds a BMus (Hons) in Music Composition and is an AWS Certified Solutions Architect. After beginning his career as a composer and educator, he transitioned into data science, bringing the same creativity and precision from his musical training to building solutions across data engineering, analytics, and cloud infrastructure.

His experience includes web scraping, real-time reporting pipelines, database design, and custom integrations using Python, SQL, Docker, and AWS. Matt has delivered complex cloud and data projects across the energy, FinOps, and hospitality sectors. He leads company strategy and technical delivery, working closely with clients from early scoping through to production.

Andrew holds a PhD in Space Physics and has more than 15 years of experience applying scientific computing, data analysis, and machine learning to real-world problems. An AWS Certified Data Engineer, Solutions Architect, and Machine Learning Engineer, he specialises in web scraping, cloud-based data solutions and custom software development.

His experience includes building ETL pipelines, automated reporting systems, machine learning models, large-scale web crawlers, and custom data collection solutions using Python, R, Playwright, Docker, AWS, and Azure. Andrew is also an accomplished trainer and speaker, with a talent for communicating complex technical concepts clearly to diverse audiences.

James is currently completing a PhD in Quantitative Psychology, applying agent-based modelling and reinforcement learning to investigate the mechanisms that generate and sustain social inequality. He specialises in data engineering, cloud data warehouse architecture, and statistical modelling using Python, SQL, DuckDB, Snowflake, and Redshift.

He has designed and implemented ELT/ETL pipelines, greenfield OLAP systems, and cloud data warehouses, processing healthcare and insurance datasets containing hundreds of billions of rows. James approaches complex technical challenges with scientific rigour, thoughtful planning, and a strong commitment to building robust, maintainable systems.

Bianca holds a PhD in Molecular Microbiology, completed a postdoctoral fellowship in pharmaceutical sciences, and is an AWS Cloud Practitioner. As a certified Carpentries Instructor and Instructor Trainer, she has delivered technical training locally and internationally in R, SQL, Python, and Git.

Her expertise includes ETL pipeline development, data visualisation, reporting, and technical documentation, with experience building cloud-based data ingestion workflows that transform raw data into analytics-ready datasets for Power BI reporting. Bianca combines almost a decade of hands-on data science experience with a proven ability to develop technical capability through practical training and mentorship.

Andri holds a PhD in Computational Astrophysics, where she developed numerical models to simulate the conditions in photoionised nebulae. She specialises in mathematical modelling, machine learning, statistical analysis, and optimisation, applying quantitative methods to a broad range of applied data science problems.

Her experience includes designing optimisation algorithms for distributed energy systems, developing machine learning models that support production applications, and using statistical methods to analyse complex datasets with Python, SQL, and C. As an AWS Certified Cloud Practitioner, Andri combines strong analytical skills with a creative approach to developing practical solutions.

Gavin holds a PhD in Ecology and has more than 10 years of experience applying statistical modelling and data analysis to complex problems. His work focuses on building reliable, reproducible data systems, with extensive experience developing ELT pipelines, automating reporting workflows, and designing and administering PostgreSQL/PostGIS databases using platforms and tools including Databricks and Nix.

He has delivered projects across the conservation, NGO, agriculture, and energy sectors, building geospatial data applications, APIs, and forecasting models for variable energy demand. Gavin takes a systems-level view, designing technical solutions that are robust, maintainable, and built to evolve over time.

Awie holds a BSc in Computing and is a certified AWS Cloud Practitioner, with over 10 years of full-stack experience spanning cloud infrastructure, backend APIs, frontend interfaces, and data pipelines. He has experience across a broad range of programming languages, including Python, TypeScript, C#, and Rust.

Awie has delivered projects across industries, including healthcare, human capital management, and higher education, processing billions of rows of data with tools like DuckDB, Polars, and Parquet, and integrating AI capabilities such as AWS Bedrock into production. Awie thrives on hard problems, picking up new tools with ease.

Shenine holds an MSc in Machine Learning and Artificial Intelligence and has more than a decade of experience delivering data science solutions across fintech, retail, and logistics. Her expertise spans machine learning, optimisation, predictive analytics, and large-scale data processing using Python, SQL, and Spark.

She has built production-ready models for applications, including time series forecasting, recommender systems, natural language processing, and computer vision, while developing robust data pipelines and cloud-based analytics solutions on AWS and GCP. Shenine combines strong analytical skills with the ability to translate technical work into insights stakeholders can act on.

Shani holds a PhD in Cardiovascular Physiology and spent over a decade as a cardiovascular researcher before transitioning into data science. Her expertise spans healthcare data analytics and engineering, database management, visualisation, reporting, and technical documentation, with experience building Python- and R-based data pipelines, managing PostgreSQL databases, and deploying containerised applications on AWS using Docker.

As an AWS Certified Cloud Practitioner, she has delivered projects across the healthcare, higher education, and technology sectors. Shani is known for her thoughtful, detail-oriented approach and her ability to balance multiple priorities while delivering high-quality technical solutions.

Monique holds a Master's degree in Bioinformatics, where she used AWS and high-performance computing to assemble complex genomes from large-scale sequencing datasets. Her expertise includes data pipeline development, database schema design, cloud infrastructure, and deployment automation, with experience building CI/CD workflows using technologies including Docker, AWS, Ansible, and Databricks.

Monique has delivered data engineering solutions across the healthcare and higher education sectors, including database migrations and systems that support production workloads. She brings precision and curiosity to her work, with a practical approach to designing robust, maintainable data solutions.

Michelle has submitted a PhD in Human Biology, where her research focused on biological age estimation from hand radiographs using computer vision and deep learning. She specialises in computer vision, machine learning, and statistical modelling, particularly in applications involving image-based data.

Her experience includes developing deep learning models for medical imaging, designing image analysis solutions for aerial imagery, and running large-scale machine learning experiments on high-performance computing infrastructure. Michelle combines careful analysis with a practical approach to developing solutions that perform reliably in real-world settings.

Kalonji holds a PhD in Molecular Biology, analysing large-scale genomic and microbial datasets using statistical modelling, high-performance computing, and reproducible computational workflows. As an AWS Certified Solutions Architect, he has experience developing data and cloud solutions using Python, R, Docker, and AWS.

His work includes contributing to a content management platform for a professional medical body, developing backend services, and creating analytical applications and visualisations using tools such as Shiny and Quarto. Kalonji combines a strong scientific foundation with practical experience across data science, software development, and the communication of technical concepts to diverse audiences.

Clarissa holds a PhD in Environmental Sciences and has more than a decade of experience in scientific research and academic publishing. She has authored more than 20 academic publications and served as a reviewer for over a dozen scientific journals, giving her extensive experience writing, evaluating, and refining technical content to the standards expected of academic publishing.

Her expertise includes statistical analysis, alongside extensive experience interpreting and communicating complex scientific and technical information. Clarissa takes a meticulous, conscientious approach, ensuring software and data documentation is clear, accurate, and accessible.