Matthew S.

I help businesses find out why complex systems and processes fail, and design the failures out before they cost money. With 25+ years in UK automotive and aerospace engineering, I bring the structured, evidence-led methods of safety-critical work to your technical and operational problems. I’m a Systems Engineer and trained Lean Six Sigma Black Belt with a BEng (Hons) in Mechanical Engineering, backed by studying for two MSc degrees in Artificial Intelligence and Applied Artificial Intelligence. FAILURE MODE AVOIDANCE & RISK ANALYSIS FMEA and failure mode avoidance, carried out before problems reach the customer Root cause investigation and operational diagnostics Identifying where a product, process or system is most likely to fail, and why Turning findings into clear, prioritised actions SYSTEMS ENGINEERING & REQUIREMENTS Requirements engineering: capturing what a system actually needs to do Systems analysis and workflow modelling Technical documentation that stands up to scrutiny PROCESS IMPROVEMENT Lean Six Sigma and DMAIC Process diagnosis and optimisation grounded in measured evidence Practical recommendations your team can implement DATA ANALYSIS & PYTHON Exploratory data analysis, statistical interpretation and reporting Data visualisation with Matplotlib Python analytical tools and bespoke applications (PySide6 / PyQt6) Machine learning and AI-assisted automation, used where they genuinely fit the problem TECHNICAL & CONTENT WRITING Engineering knowledge is only useful if people can understand it. I write clear, accurate content for technical and non-technical readers: Technical articles, explainers and guides Process documentation and reports Content on engineering, systems, quality, data and AI topics Editing and restructuring existing technical material for clarity AI VOICE & DATA ANNOTATION I also support AI development with careful, consistent annotation work: Voice and audio annotation, transcription and review Evaluating and rating AI-generated responses against guidelines Quality checking of labelled datasets Following detailed annotation specifications with attention to accuracy and consistency My AI and data science background means I understand why annotation quality matters to the models built from it. ENGINEERING BACKGROUND I spent over two decades as a freelance engineer across UK automotive and aerospace. Clients and associated organisations included Lotus Engineering, Jaguar, Land Rover, Bentley Motors, Rolls-Royce, MG, Ford, Bosch Engineering and Caterpillar. My final industry roles: Senior Analysis Engineer, ADAS / Autonomous Vehicles Lead Application Engineer, Hybrid and Electrified Commercial Vehicles Software Subject Matter Expert, Advanced Control Systems These meant working across disciplines on complex systems and presenting critical findings to senior stakeholders. I’ve also built a bespoke Python application for forensic evidence handling in legal contexts, where data integrity, traceability and documentation had to be right. HOW I WORK Understand the problem before choosing a tool or technology. Ask where it could fail, and why, before it does. Base decisions on evidence, not assumptions. Communicate findings clearly to technical and non-technical people. Good engineering isn’t just making something work. It’s understanding why it works, where it might fail, and making sure the result is reliable and fit for purpose. Clear thinking. Sound engineering. Failures designed out.