Is a senior data science professional with over 10 years of experience in implementing predictive models that deliver actionable insights, improve business outcomes, and expand industry knowledge. Daniel's past projects have delivered over $1M in incremental monthly revenue for prior telecom clients.
Experienced in machine learning and data analytics, Daniel has excellent verbal, written and visual communication skills to effectively relay findings to business leaders and multidisciplinary stakeholders.
Daniel holds a Bachelor's Degree in Mathematics from Brandeis University.