Sean Marandure

I am an Automation Developer building production-grade Python systems for ERP and product configurator environments, alongside an MSc in Data Science & Advanced Computing (AI/ML & Big Data). My work focuses on architecting control layers, automating rule-based systems, and integrating relational databases with configurable product platforms. With a foundation in engineering and CAD automation (Autodesk Inventor iLogic, VB.NET), I transitioned into software development to design scalable, version-controlled tooling that bridges engineering logic with modern data workflows. My long-term research interests lie in machine learning systems, optimisation, and quantum-accelerated approaches to complex decision environments.

Architected a modular Python CLI application designed to version-control enterprise systems. The project involved parsing raw data structures, managing relational database state, and enabling reproducible automation pipelines within a legacy environment.

Currently developing a MapReduce-style distributed processing framework to coordinate parallel map and reduce workers over partitioned datasets. The system implements task scheduling, intermediate key-value shuffling, and process communication to simulate large-scale data processing workflows. This project is strengthening my understanding of distributed computation, system coordination, and data-intensive architecture design.

Participated in a timed, scenario-based AWS cloud simulation focused on diagnosing and resolving distributed system failures under pressure. Worked across services including IAM, EC2, S3, RDS, and CloudWatch to debug misconfigurations, investigate scaling issues, and restore system functionality. The experience strengthened my understanding of cloud architecture, observability, and infrastructure-level problem solving, principles directly applicable to scalable data and automation systems.

Python • NumPy • SymPy

An educational tool to assist in solving linear systems using matrix transformations (Gaussian elimination, inverse computation). Built while completing Coursera’s Mathematics for Machine Learning.

GitHub Repo →

ANSYS Fluent • Python • TensorFlow

CFD-generated dataset used to train an ANN to interpolate wind velocity and predict optimal building geometries for pedestrian comfort. Validated simulations with real weather data.

Autodesk Inventor • iLogic (VB.NET)

Rule-based parametric model: clamps width/height, conditionally suppresses features (vision panel, seals), and writes iProperties for BOM and drawings.

Python • Postman • SQLAlchemy (Object Relational Mapping) • SQLite (Lightweight Relational Database, Schema Design & Querying) • Flask & APIs

A lightweight MVP Flask app, originally built to streamline workplace task management by replacing email-based task lists. The project has since evolved into a broader vision: a fully functional productivity application designed for students and professionals alike. Built with Python, Flask, SQLAlchemy, and SQLite, the app emphasises clean API design, database integration, and scalable feature development.