Daniel Gloven
Principal Data Engineer
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDaniel Gloven is a Principal Data Engineer with a decade of experience building scalable data and ML systems, currently leading Player Health & Safety analytics at the NFL in New York. He transitioned from physics-informed numerical methods (Ph.D.-level work at UC Berkeley) into production data science and engineering, applying rigorous modeling techniques to real-world product problems. At AirDNA he was the first U.S. hire, scaling ML-driven products and pipelines across millions of short-term rental listings and helping the company through acquisition. He combines big-data engineering (Spark, Snowflake, Airflow) with hands-on model development for pricing, AVM, and forecasting, and has a history of automating end-to-end systems. Colleagues rely on him for turning research-grade methods into robust, maintainable services that support business-critical decisions.
10 years of coding experience
12 years of employment as a software developer
B.S. Mechanical Engineering, B.S. Mechanical Engineering at University of California, BerkeleyData Science Immersive, Data Science Immersive at Galvanize Inc
Github Skills (18)
mpi10
cluster-computing10
hpc10
release-it10
petsc10
openmp10
snl-applications10
parallel-computing10
amr10
multiphysics10
scientific-computing10
patch9
middleware9
documented9
fortran8
Programming languages (3)
Github contributions (5)
applied-numerical-algorithms-group-lbnl/Chombo_4
Jun 2019 - Feb 2023
This version of Chombo is fortran-free and depends on the Proto middleware infrastructure for performance portability.
Contributions:1066 commits, 4 PRs, 1075 pushes in 3 years 8 months
fortranmiddleware
applied-numerical-algorithms-group-lbnl/Chombo_3.2
Jul 2019 - Jan 2023
The is the Chombo 3.2 (patch 8) release. It is stable and well documented.
Contributions:53 commits, 2 PRs, 253 pushes in 3 years 7 months
patchdocumentedchomborelease-itwell-documented
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