Daniel Redmond

Daniel Redmond has had extensive work experience in various roles related to artificial intelligence, machine learning, and data science. Their most recent position as Principal Machine Learning Engineer at Cision demonstrates their expertise in this field. Prior to that, they served as a Key Adviser for AI and Machine Learning at Recko, Inc. from 2019 to 2022.

From 2016 to 2022, Redmond worked as a Lead Data Scientist at ADS Environmental Services, where they contributed to data analysis and decision-making processes. Before that, they held the role of VP of Data Science and Machine Learning at Bark from 2015 to 2022, where they played a significant role in utilizing data science and machine learning techniques to enhance business operations.

Redmond's experience also includes working as a Lead Data Scientist at Ahalogy from 2014 to 2015, where they demonstrated strong analytical skills. Prior to that, they served as the Chief Architect at InfiSafe from 2013 to 2014, leading the development of Big Data solutions for online gaming, including ETL parsing, machine learning, and pattern analysis.

Redmond's early career consisted of roles as a Mathematician and Computer Scientist at Frame Research Center from 2007 to 2013, and as a Software Consultant at Microsoft from 2002 to 2003. Daniel began their professional journey as a Consultant at AT&T GIS from 1995 to 1996.

Overall, Daniel Redmond has a diverse and extensive background in AI, machine learning, and data science across various industries and organizations.

Daniel Redmond earned a Bachelor of Science (B.S.) degree in Computer Science from Missouri University of Science and Technology from 1993 to 1998. Daniel then pursued further education at the University of Missouri-Columbia from 1999 to 2009, where they obtained a Doctor of Philosophy (Ph.D.) degree in Mathematics.