Ryan Low
About Ryan Low
Ryan Low is a Data Engineer with a background in Chemistry and Biological Chemistry. He has worked at ThoughtWorks since 2021 and has experience in various roles, including quality assurance and sales operations, across several organizations.
Work at ThoughtWorks
Ryan Low has been employed at ThoughtWorks as a Data Engineer since 2021. In this role, he focuses on data engineering tasks, leveraging his expertise in machine learning and data visualization. His work involves utilizing tools such as TensorFlow and Keras for model development, as well as managing databases with SQLAlchemy and PostgreSQL. Ryan's contributions to ThoughtWorks reflect his commitment to advancing data-driven solutions.
Previous Experience at Novartis
Before joining ThoughtWorks, Ryan Low worked as a Quality Assurance Intern at Novartis in Singapore for five months in 2018. This internship provided him with valuable experience in quality assurance processes within the pharmaceutical industry, enhancing his understanding of compliance and operational standards.
Education and Expertise
Ryan Low holds a Bachelor of Science in Chemistry and Biological Chemistry from Nanyang Technological University, where he studied from 2014 to 2018. He also earned a Diploma in Pharmaceutical Sciences from Ngee Ann Polytechnic, completing his studies from 2009 to 2012. Additionally, he obtained a Professional Certificate in Data Science from the Institute of Data in 2021, further solidifying his expertise in data-related fields.
Experience at CoAssets Ltd.
Ryan Low's tenure at CoAssets Ltd. spanned from 2018 to 2020, during which he held multiple roles. He began as a User Engagement Executive, later becoming a User Engagement Manager for six months in 2019, and also served in Sales Operations for one year. His roles involved enhancing user engagement and operational efficiency within the company.
Skills in Data Science and Engineering
Ryan Low specializes in various data science and engineering tools. He employs TensorFlow and Keras for machine learning model development and utilizes Seaborn and Matplotlib for data visualization projects. Additionally, he is experienced in using Circle CI for continuous integration and deployment, and Docker for containerization, which are essential for modern data engineering workflows.