Caden Hariz

I am an analytical and curious Data & AI engineer with experience delivering end-to-end data solutions for enterprise clients as well as in clinical & research settings. I combine machine learning, data engineering, and statistical programming with strong stakeholder management and consulting skills.

At Capgemini Invent I designed target-state data architectures, developed ML use cases for anomaly detection and standardisation, and built cloud-native AI-enabled data acquisition workflows on Microsoft Azure. I also prototyped database migration solutions and led performance optimisation efforts.

My earlier roles include clinical work as a registered nurse and researcher at Purdue University, where I automated Python-based scoring tools that reduced data collection and processing time by 70%. I hold postgraduate study in Information Technology (AI specialisation) and a Master in Nursing Science with digital health expertise.

I am passionate about sustainable, accessible, evidence-based technology and enjoy mentoring and facilitating learning in ML, AI architecture, and NLP—seeking roles that combine technical impact, collaboration, and meaningful stakeholder engagement.