About

Joann Chen is a highly skilled and passionate data scientist and software engineer with a strong background in cloud computing, machine learning, and deep learning. She is currently pursuing an M.S. degree in Computational Data Science at Carnegie Mellon University's School of Computer Science and has over 1.35 years of relevant experience in the industry. Joann has a proven track record of designing and deploying cloud-based systems, building data pipelines, and developing machine learning models to solve complex problems. She has worked as a Software Engineer, Machine Learning at Twitter's Home Timeline team, where she has been responsible for developing scalable systems and implementing data-driven solutions. Prior to her current role, Joann worked as a Software Engineer Intern at Uber's Advanced Technology Group, where she designed and deployed an end-to-end CI/CD log classification system, automated services setup with Terraform modules, and implemented data pipelines with AWS services. She also worked as a Data Science Research Intern at The Scripps Research Institute, where she processed large-scale human genome data and built and assessed machine learning models to predict the biological effect of regulatory variants. Joann is highly skilled in software development, cloud computing, data science at scale, machine learning, and deep learning. She is proficient in Python, Java, Spark, SQL, and has experience using TensorFlow, PyTorch, Hadoop, Kafka, GCP, and Kubernetes. Joann is also an experienced freelance photographer and is known for her creativity, compassion, determination, and persistence. Joann is always eager to learn, collaborate, and create. She is open to discussing software engineering, designing scalable systems, data science, AI, and anything else that piques her interest. If you're interested in working with Joann or chatting with her about her work, send her a message.