Santona Tuli, Ph.D.
About Santona Tuli, Ph.D.
Santona Tuli, Ph.D., serves as the Head/Director of Data at Upsolver, where she drives strategy for data lake and workflow authoring frameworks. With extensive experience in data science and research, she has held positions at notable organizations including CERN and UC Davis, contributing to advancements in data processing and analytics.
Current Role at Upsolver
Santona Tuli serves as the Head/Director of Data at Upsolver, a position held since 2023. In this role, Tuli drives strategy for data lake and workflow authoring frameworks, focusing on enhancing the developer experience with the company's products. Tuli's leadership emphasizes the importance of effective communication in data science, ensuring that technical concepts are accessible to diverse audiences.
Previous Experience at Upsolver
Prior to the current role, Santona Tuli worked at Upsolver as a Principal Product Manager for four months in 2022. During this time, Tuli contributed to product development and strategy, leveraging extensive experience in data management and analytics to enhance Upsolver's offerings.
Academic Background and Qualifications
Santona Tuli holds a Doctor of Philosophy (Ph.D.) in Physics, Nuclear Sciences, and Quantum Chromodynamics from the University of California, Davis, achieved between 2014 and 2019. Tuli also earned a Bachelor's Degree in Physics and Mathematics from Trinity University from 2009 to 2013. This strong academic foundation supports Tuli's expertise in data science and analytics.
Professional Experience at CERN
From 2015 to 2021, Santona Tuli worked as a Research Data Scientist at CERN in Geneva, Switzerland. Tuli led a team of data physicists to measure a rare particle family in proton-nucleus collisions, contributing valuable insights into the strong nuclear force theory. This role underscored Tuli's capability in managing complex data-driven projects in a high-stakes research environment.
Contributions to Data Science and Technology
Santona Tuli has played a significant role in enhancing Apache Airflow by simplifying its usage and developing additional tools for enterprise data orchestration. Tuli also developed machine learning pipelines for natural language query understanding in the CRM space, demonstrating expertise in handling enterprise-level data at scale. These contributions reflect a commitment to advancing data science practices and technologies.