Analytical and detail-driven Mechanical Design Engineer with over 5 years of experience transitioning into data analytics, with a strong foundation in problem-solving, statistical modelling, and process optimisation. I have led tolerance stack analyses, sealing verifications, and statistical process capability studies across injection-moulded medical device components, using Monte Carlo simulations and Python-based data analysis to quantify design robustness and manufacturing variability.
I have developed and automated datasets in Excel and Python to model dimensional variation, simulate risk outcomes, and support design verification under ISO 13485 and ISO 14971 frameworks. Experienced in working within Greenlight Guru eQMS, I have produced risk analyses, DHF documentation, and statistical summaries used in design reviews and regulatory submissions. My background combines strong technical foundations in mechanical systems with practical data analytics — from using Python for predictive modelling to optimising test data interpretation and simulation workflows — and I am now focused on expanding this analytical expertise into dedicated data analyst roles where I can drive insight, efficiency, and informed decision-making through data.
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