Description

I’m a Python engineer who builds backend systems for complex, data-driven problems.

With a background in astrophysics, I specialise in turning abstract logic — from scientific papers, mathematical models, or loosely defined ideas — into clear, reliable, production-ready code.

I design systems that go beyond quick scripts or dashboards: structured, maintainable applications that process and make sense of complex data.

What I typically work on:

Backend systems and services in Python
APIs and data processing workflows
Translating models and algorithms into robust implementations

I write correct, clean code designed to scale — configurable, extensible, and built to last.

If you need someone who can take a complex idea and turn it into something that actually works, let’s talk.

Industry field of expertise

Languages

English
Native or bilingual
Maltese
Native or bilingual
Italian
Conversational
Spanish
Fluent

Workplace preferences

Remote only

Primarily works remotely

Freelance
Freelance Scientific Software Developer
November 2018 - Today (7 years and 8 months)
Delivered backend systems, data pipelines, and production Python software for research-driven and data-intensive applications.

End-to-end ownership: design, implementation, client alignment, and deployment.

Long-Term Core Project: Data Pipeline & Indexing Platform (Apr 2022 – Present)

Independently designed and evolved a platform constructing economic indices from large-scale global news datasets.

▪ Built a configuration-driven framework enabling non-developers to define new indices without modifying code
▪ Designed resilient data ingestion and transformation pipelines with explicit validation and failure handling
▪ Implemented published methods for index construction into reliable, testable systems
▪ Developed robust automation workflows for large-scale historical data collection
▪ Evolved the system over multiple years into stable, production-grade infrastructure

Other Selected Work:
▪ Simulation systems (agent-based, multithreaded, epidemiological models)
▪ Numerical optimisation and modelling (ODE/PDE systems)
▪ Data analysis pipelines and visualisation workflows
▪ Implementation of methods from academic literature without reference implementations
▪ Technical documentation and reproducible workflows

▪ Work often involves implementing methods directly from academic literature where no reference implementation exists
Python Back-End development software architect Data science Data visualization
Onna
Python Developer
DIGITAL AND IT
June 2020 - February 2022 (1 year and 8 months)
Barcelona, Spain
Worked on large-scale data ingestion and backend systems supporting eDiscovery and compliance use cases.
• ▪ Contributed to 20+ third-party APIs for large-scale ingestion (billions of files, multi-petabyte datasets)
• ▪ Designed efficient data synchronisation logic, reducing API usage while maintaining completeness
• ▪ Observability and monitoring (metrics, dashboards, system diagnostics)
• ▪ Refactored backend services to improve readability, testability, and maintainability
• ▪ Contributed to CI/CD improvements and system modularisation
API Back-End development Python software architect Docker
Sherpa Management Services
Junior Developer & Mathematician
BANKING AND INSURANCE
October 2016 - October 2017 (1 year)
Naxxar, Malta
• ▪ Co-authored a mathematical research paper proposing a novel approach to quantifying insurance risk
• ▪ Translated mathematical models into production code, with careful attention to numerical stability and model validity
• ▪ Contributed to the design of a Python-based system modelling financial risk and lifecycle outcomes
• ▪ Developed REST APIs to expose computational models
• ▪ Integrated backend systems with structured financial data
• ▪ Improved code quality through testing, refactoring, and performance optimisation
• ▪ Produced technical documentation for internal and external use
Python API Data science software architect Data visualization