Machine Learning · Mathematics · Long Island

Building systems that make decisions at scale.

Tech Lead MLE at Meta. PhD in Mathematics. I build machine learning systems at scale and lead the teams behind them, turning complex research problems into measurable business impact.

Work history LinkedIn Writing

About

I'm a machine learning engineer and tech lead who has spent the last decade building systems that make high-stakes decisions at scale: recommendation engines, pricing models, ranking systems, and paywall algorithms.

Currently at Meta on the Ads team, where I own multi-objective ranking architecture and drive new product delivery across surfaces. Before that I built and led data science orgs at Peacock, SeatGeek, The New York Times, and Plated.

My background is in mathematics. I did my PhD at the University of Tennessee on persistence diagrams and topological data analysis. I gravitate toward problems where the research is rigorous and the business impact is concrete.

Outside of work I mentor people breaking into data science and ML. I live on Long Island with my family.

Currently
Tech Lead MLE, Meta Ads
Education
PhD Mathematics, UTK
BS Mathematics, Stony Brook
Expertise
Ads ranking, causal inference, experimentation, auction theory
Mentoring
GrowthMentor · SharpestMinds · TeamUp
Based in
Long Island, NY

Experience

Where I've worked

Meta
Nov 2024 – Present
Machine Learning Engineer, Tech Lead
Building and owning multi-objective Ads ranking architecture responsible for $150M+ in incremental revenue. Drive pacing, calibration, and delivery logic for new ad products across all surfaces. Tech lead across multiple high-priority initiatives.
Peacock (NBCU)
Aug 2022 – Nov 2024
Director of Data Science
Built and led a cross-functional org of Data Scientists and MLEs. Shipped churn prediction and lifecycle models with multi-million dollar annual CLV impact. Partnered with C-suite on pricing strategy using causal inference and ran the GenAI personalization roadmap.
SeatGeek
Jun 2021 – Aug 2022
Lead Data Scientist
Built production models for dynamic pricing and customer segmentation. Owned the internal A/B testing platform end to end.
The New York Times
Mar 2019 – Jun 2021
Senior Data Scientist
Developed novel paywall algorithms using causal ML and randomized controlled experiments. Built production models across churn, conversion, sentiment, and engagement.
Plated
Aug 2017 – Feb 2019
Data Scientist
Built recommendation and demand forecasting models. Led DS/ML recruiting and ran academic outreach at NYU and Cornell Tech.

Research

Publications

Signal classification with a point process distance on the space of persistence diagrams
Advances in Data Analysis and Classification, 2018 · Marchese & Maroulas
K-means clustering on the space of persistence diagrams
Wavelets and Sparsity XVII, SPIE, 2017 · Marchese, Maroulas & Mike
Topological learning for acoustic signal identification
FUSION 2016 · Marchese & Maroulas
Probability Matrices
Encyclopedia of Social Network Analysis and Mining, 2nd Ed., Springer, 2016 · Maroulas & Marchese

Writing

Musings

Occasional writing on machine learning, building teams, and mathematics. No set cadence, just when something is worth saying.

✦   Posts coming soon   ✦