Joshua Demeo
About Joshua Demeo
Joshua Demeo is a Data Science Manager IV at Tatari, where he has worked since 2020. He has a diverse background in data analysis, medicinal chemistry, and research, with experience at various institutions including Takeda Pharmaceuticals and Caltech.
Current Role at Tatari
Joshua Demeo serves as DS Manager IV at Tatari, a position he has held since 2020. In this role, he is responsible for overseeing data science initiatives and managing projects that leverage data analytics to enhance marketing strategies. His work focuses on developing methodologies for ad attribution, particularly in relation to incremental and view-through metrics, which are essential for optimizing marketing campaigns on both linear and streaming television platforms.
Previous Experience in Data Science and Research
Joshua has a diverse background in data science and research. He worked as a Data Scientist at Genius Sports for six months in 2019, where he applied data analytics to sports-related data. Prior to that, he served as a Consultant in Data Analytics at Control Risks for four months in 2019, focusing on economic and political risk analysis. His experience also includes roles as a Research Associate in Medicinal Chemistry at Takeda Pharmaceuticals and Sirenas Marine Discovery, where he contributed to various research projects from 2014 to 2017.
Educational Background
Joshua Demeo earned a Master of Science in Analytics from the Georgia Institute of Technology, completing his studies from 2018 to 2019. He also holds a Bachelor of Science in Biochemistry from the University of California, Los Angeles, where he studied from 2009 to 2013. His educational background provides a strong foundation for his work in data science and analytics.
Technical Skills and Proficiencies
Joshua is proficient in several programming and data analysis tools, including Python, SQL, and Tableau. These skills enable him to perform complex data analysis and visualization tasks effectively. He also utilizes natural language processing (NLP) techniques to analyze conflicts-of-interest and corruption networks, showcasing his capability in handling intricate data challenges.
Research Experience and Contributions
Joshua's research experience includes a role as a Graduate Student Researcher at Caltech, where he worked for five months in 2014. Additionally, he was an Undergraduate Researcher at UCLA from 2011 to 2013. His contributions to research in medicinal chemistry and data analytics have been significant, particularly in applying machine learning techniques to economic and political risk analysis.