Nora Eisner, PhD
Project Management | Data Science | Quantitative research | Time-series analysis | Astrophysics | Video + Podcast Host
About me
I’m a Senior Research Data Scientist at Tatari, where I leverage machine learning and statistical modelling to enhance predictive performance in TV and streaming ad measurement. My work focuses on optimising ad allocation, improving forecasting models, and developing data-driven solutions for creative and baseline performance analysis.
During my astrophysics Ph.D. at the University of Oxford, I specialized in developing novel and unconventional methods to detect planets beyond our solar system. I spearheaded a global citizen science project, which I continued to run for over five years. At the Centre for Computational Astrophysics, I applied advanced statistical techniques to analyze time-series data.
With experience spanning project management, data science, and software development, I excel in algorithm design, statistical analysis—particularly Bayesian inference—and managing large-scale projects. My expertise lies in navigating high-dimensional parameter spaces and driving innovation in global science platforms through cutting-edge software solutions.
When not at my desk, I can often be found near a coffee machine.
Themes
Example: I designed, built, and continue to manage a global non-profit project designed to analyse time-series data with a global community of citizen scientists.
Example: Built a generalized model that predicts the observable effects of three-body dynamics in multiple types of astronomical time-series data, using symbolic coding tools including pyMC.
Example: Developed user-friendly, open-source data analysis tool in Python that automatically generates diagnostic reports to identify signals in time-series data.
Example: I identify and tackle scientific problems using quantitative research. This work has been published in numerous peer reviewed journals.