Bio

The possibilities and potential business value of analytics are endless, which is why companies have spent the last decade investing in the right people, data, processes and enabling technology. However, despite such intensive investment: - Less than 50% of the best models get deployed. - 90% of models take more than three months to deploy. - 44% of models take over seven months to be put into production. Then, the inability to put analytics into action is one of the biggest challenges across industries. As a problem solver, I work every day for efficiently moving analytic models from development into deployment at scale. By collaborating with data scientists, data engineers, IT developers and source system experts, we design and prototype machine learning systems for delivering expected business value. By enabling these groups to work with a shared understanding of the stakeholders’ purpose, we support ModelOps as the holistic approach for dealing with analytics operationalization.