Allen Amos Binks
About Allen Amos Binks
Allen Amos Binks is a Data Science Lead at Immutable, where he has worked since 2022, focusing on data science applications in blockchain gaming. He has a diverse background in consulting and data science, with previous roles at Deloitte Australia and Oliver Wyman.
Work at Immutable X
Allen Amos Binks serves as the Data Science Lead at Immutable X, a position he has held since 2022. In this role, he specializes in building foundational data science elements for blockchain games, particularly for the game Gods Unchained. His responsibilities include defining game economy metrics such as Lifetime Value (LTV) and developing frameworks for experimentation. He also establishes baseline statistical models to support data-driven decision-making in the gaming industry.
Previous Experience in Consulting
Prior to his current role, Allen worked at Deloitte Australia as a Consultant from 2015 to 2016. He later returned to Deloitte as a Senior Consultant from 2016 to 2017. His experience also includes positions at Oliver Wyman, where he served as a Labs Consultant in 2017, a Lead Data Scientist from 2020 to 2022, and a Senior Labs Consultant in 2018. His consulting roles involved providing data-driven insights and solutions to various clients.
Background in Software Engineering
Allen began his career as a Software Engineer at Ciena from 2013 to 2014 in Ottawa, Canada. This role provided him with foundational skills in software development, which he later applied in his data science and consulting positions. His technical background supports his expertise in data science and analytics within the gaming sector.
Education and Expertise
Allen holds a Master of Applied Science in Computer Engineering from Carleton University, which he completed from 2012 to 2014. He also earned a Bachelor of Engineering (B.Eng.) in Electrical and Electronics Engineering from the same institution, studying from 2006 to 2011. His educational background equips him with a strong foundation in engineering principles, data analysis, and statistical modeling.