Emma Castiglia

About Emma Castiglia

I am interested in applying machine learning and other models to solve industry\'s leading problems. At Meta, I worked with the Privacy team to create metrics and apply ML to ensure promises about user data were being upheld and with the Wearables System Health team to optimize battery life on our devices. At Netflix, I trained a time-series model to predict requests to the servers to scale the system more efficiently, while reducing costs and wait-times. Before moving to industry, I obtained a PhD in particle physics at Yale. My dissertation focused on incorporating machine learning algorithms into both the experiment\'s trigger system and analysis of signal events. I enjoy analyzing data and pulling out actionable insights and am excited to continue to build upon my research and data science skills.

Experience

1. Data Scientist

   Meta

   Aug 2022 — Present · New York, NY, US

   Data Scientist within Reality Labs | Wearables | System HealthI was the analytics lead for improving and maintaining power and thermal targets across our wearable devices.Responsibilities included- Unified topline metrics and logging schema across all devices- Ensured quality experiences for users on the device due to power/thermal- Improved in-field power measurements to allow for precise trend tracking and debugging- Defined and optimized a user\'s typical day of use to ensure sufficient battery life; created 3 user profiles with varying behaviors on the device- Conducted deep dive analyses to understand the main drivers of low battery shutdowns Research Data Scientist within Infrastructure Data Science focusing on PrivacyWhile working in privacy, I defined key metrics for the privacy program, applied and monitored ML models for privacy related projects, and collaborated with SWEs, DEs, PMs, and lawyers to ensure our user-data promises were upheld. I was able to gain industry experience as a data scientist, provide insight on important metrics, and work with partners to prioritize and complete projects on their roadmaps.Responsibilities included- Prototyping a pipeline applying ML to find privacy commitments in external sources reducing manual hours, comparing vendors with formal study, and reviewing legal contracts for technical requirements- Pioneering creation of a transparent commitments risk score to prioritize actions to reduce risk- Executing a formal study and creating methods for monitoring ML model performance in privacy systems- Creating and maintaining data pipelines for Commitments- Developed tooling and data visualization for the Regulatory Readiness team

Education

• Yale University

  Doctor of Philosophy - PhD, Particle Physics

  2016 — 2022

• Yale University

  Master of Philosophy - MPhil, Physics

  2016 — 2020

• Needham High School

  High School

  2009 — 2012

• University of Chicago

  Bachelor’s Degree, Physics and Mathematics

  2012 — 2016

Skills

• Tmva
• Keras
• Python
• Research
• Tensorflow
• C++
• Physics
• Mathematics
• Root
• Data Analysis
• Monte Carlo Simulation
• Powerpoint
• Microsoft Excel