As a Solution Architect at Tempus, I work on the Lens platform for oncology data science, designing and implementing solutions that leverage the power of AI and big data to advance cancer research and care. I collaborate with cross-functional teams of engineers, scientists, and clinicians to deliver high-quality and scalable products that meet the needs of our clients and partners.I graduated from Harvard University with a master's degree in Computational Biology and Quantitative Genetics, where I also cross-registered at MIT for courses in applied ML. I have a strong background in physics, with a master's degree from the University of Manchester and a study abroad year at the University of Toronto. I have multiple research collaborations with forthcoming publications on topics such as unsupervised learning in Alzheimer's, survival prediction in computational models of cancer immunity, and metric development to predict burnout from EHR usage, following research internships at MGH, BioMarin, and Genentech, I am proficient in Python, pandas, scikit-learn, TensorFlow, and other data science tools and frameworks.I am passionate about the interdisciplinary frontiers of technology and the life sciences, and motivated by the discovery of hidden stories from data. I enjoy applying machine learning, statistics, and computational approaches to solve problems in technology and digital health. I am always eager to learn new skills, explore new domains, and collaborate with diverse and talented teams.