Summary
Klevis Aliaj is a Solutions Architect with a decade of hands-on experience building data-driven systems, machine learning models, and automation frameworks across enterprise and academic settings. He has driven measurable business impact—most notably a project that improved profit margins by 35% while boosting campaign quality—and led cloud data science platform evaluations and POCs involving AWS and Databricks. His background blends a PhD in Bioengineering with production engineering at companies like Dell and CA Technologies, enabling him to translate complex research techniques (Bayesian inference, Kalman filters, DTW) into robust, deployable solutions. He routinely ships readable, efficient code and has experience creating visualization and web tools to make models actionable for stakeholders. Klevis is a clear communicator and active collaborator who pairs meticulous technical design with practical product sensibilities. An under-the-radar strength is his patent-pending work on multivariate data sketches, reflecting a focus on concise summaries of large datasets for scalable analytics.
9 years of coding experience
17 years of employment as a software developer
Bachelor of Science Biomedical/Medical Engineering, Bachelor of Science Biomedical/Medical Engineering at The University of Texas at Austin
The University of Utah
Spanish, Albanian