Teresa Datta is a seasoned Machine Learning Research Scientist currently at Arthur since July 2022 and also serves as the Resources & Community Lead for Women in Data Science (WiDS) Worldwide since June 2022. Previously, Teresa contributed as a Research Assistant at Harvard University from August 2021 to July 2022 and gained experience as a Data Science Intern at Spotify in mid-2021. Early career roles include a Disinformation Assembly Student Fellow at the Berkman Klein Center for Internet & Society, a Data Fellow at Bluebonnet Data, and a Data Solutions Technology Intern at Johnson & Johnson, among others. Teresa holds a Master of Science in Data Science from Harvard University and a Bachelor of Arts summa cum laude in Chemistry with a minor in Computer Science from Cornell University, complemented by a brief educational stint at the University of Oxford.
Arthur AI
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Arthur is a proactive model monitoring solution that gives you the confidence that your AI deployments are performing as expected, and the peace of mind that you can catch and fix issues before they derail your models. With advanced performance monitoring, bias detection, and customizable alerts, you’ll never miss an issue; and Arthur’s explainability engine makes runtime debugging a breeze with prediction-level explanations, even for black box models. No matter where your models are deployed, Arthur brings them all into view in a centralized platform. Give your data science team the freedom to use whichever deployment frameworks and engines they want, with the knowledge that you’ll be able to monitor models anywhere with just a single line of code.