I am a Senior Experimental Data Scientist specializing in Ad Tech. I design, execute, and analyze experiments focused on case-specific advertising metrics to guide critical product decisions. I also create scalable statistical models that optimize timing, pricing, shaping, and other auction dynamics within the ad tech stack. I believe that my background in experimental design and my experience in applying it to ad tech positions me to drive increased reach, ad spend and auction efficiency in this industry.
Pandas, NumPy, scikit-learn, Keras, tensorflow.
Regression, k-means, stichastic techniques, NLP.
SQLite, Hadoop, Snowflake, ROOT.
Extract and clearly communicate recommendations.
Tableau, MatPlotLib, seaborn
Hypothesis testing, robust result and uncertainty analysis.
A:B/Multivariate testing, pulse testing. Ensure robust and statistically significant results that are actionable and scalable.
Optimize over 1T ad requests daily. Interact internally with product experts and externally with Publishers, DSPs and independent market authorities giving me a unique perspective into the ad tech industry.
I have created and productionized algorithms that optimize auction timing, set take rates dynamically and prioritize valuable ad sizes, maximizing ad spend.
Collaborate with a diverse range of stakeholders. I interpret requirements, suggest improvements, communicate results and deliver solutions effectively and clearly..
Excellent inter-audience communication skills demonstrated through multiple publications as well as invited talks and chair opportunities at national and international conferences.
I have led data science teams on multiple projects. I enjoy motivating team members to be their best by setting targets and delegating tasks based on their abilities and skills.
Ph.D - Nuclear Physics, 2021
Rutgers University
MPhys - Physics, 2016
University of Surrey, UK
Senior Data Scientist, July 2024 - present
Magnite
Data Scientist, 2022 - June 2024
Magnite
Experimental Data Analyst (Post-Doc), 2020 - 2022
Rutgers University / Oak Ridge National Laboratory
Internship - Detector Diagnostics Specialist, 2018
Lawrence Livermore National Laboratory
Resident Graduate Student, 2017 - 2020
Oak Ridge National Laboratory
Machine Learning Course, 2021
Stanford University - Andrew Ng (online)
Relational Databases and SQL, 2022
Stanford University (online)