Josh Howes
About Josh Howes
Josh Howes is the Senior Director of Data Science & Machine Learning Engineering at Cision, with extensive experience in data science roles across various companies.
Title and Current Company
Josh Howes is the Senior Director of Data Science & Machine Learning Engineering at Cision. In this role, he leads a team responsible for developing advanced classifiers, sentiment models, and semantic similarity systems. His team has also implemented a comprehensive MLOps infrastructure to support the deployment of thousands of models into production.
Career at Valassis
Josh Howes worked at Valassis as a Distinguished Data Scientist for two months in 2021. Prior to this, he served as the Senior Principal Data Scientist from 2018 to 2021, based in the Raleigh-Durham, North Carolina Area. During this tenure, he led multiple data-driven projects focusing on cost-saving and automation initiatives.
Previous Roles and Locations
From 2017 to 2018, Josh Howes was a Senior Data Engineer at Citadel LLC in Raleigh, North Carolina. He held the position of Senior Data Scientist at Xometry in Raleigh-Durham, North Carolina Area from 2016 to 2017. Before that, he occupied various roles at MaxPoint including Senior Manager and Senior Data Scientist between 2013 and 2016. Josh also worked at Accenture Technology Labs as an R&D Manager in the Washington D.C. Metro Area from 2011 to 2013.
Educational Background
Josh Howes earned his Master's degree in Information Systems from the University of Maryland Baltimore County in 2010. He completed his Bachelor's degree in Economics from the University of North Carolina at Chapel Hill in 2005.
Professional Contributions at Cision
At Cision, Josh Howes led several key initiatives. He coached a distributed team of over 20 professionals in data science and machine learning engineering. His leadership helped in identifying cross-functional opportunities to apply machine learning for business improvements and enhancing customer experience. He also spearheaded projects concentrated on external-facing product features and efficiency improvements.