
Until recently, I was a technologist in the enforcement division of the Consumer Financial Protection Bureau (CFPB) working to hold companies accountable for unfair, deceptive, or abusive practices towards consumers.
I also taught a Python-based geospatial data science course in the Masters of Urban Spatial Analytics program at the University of Pennsylvania from 2019 to 2023. Course materials for the latest iteration of the course are available on Github .
Prior to working at the CFPB, I was the director of the Finance, Policy, and Data unit in the Office of the City Controller in Philadelphia under City Controller Rebecca Rhynhart. My team worked to produce data-driven, objective analysis of issues with financial impact for the City of Philadelphia and improve transparency around the City's spending of taxpayer dollars.
I am passionate about data visualization, predictive analytics, and effective communication of complex ideas to a broad audience. I am a strong supporter of transparency in government, open-source software, and the open science framework.
I'm an astrophysics Ph.D. graduate from UC Berkeley, where I studied the Universe as a National Science Foundation Graduate Research Fellow. My dissertation research focused on cosmology, and in particular, the study of the large-scale structure of the Universe. One of my most exciting research achievements involved leading a team that measured the kinematic Sunyaev-Zel'dovich effect for the first time ever .
I graduated from Princeton in 2011 with a B.A. in astrophysics and a certificate in the applications of computing. When not analyzing interesting data sets, I enjoy gardening, reading, running long distances, and watching and playing baseball.

Mapping Philadelphia's Gun Violence
An interactive app mapping shooting victims in Philadelphia for the current year, updated daily, with historical data dating back to 2015.

Parking Jawn
An interactive dashboard allowing users to explore parking violations in Philadelphia from 2012 to 2017.

MUSA 550: Geospatial Data Science in Python
The course materials for MUSA 550, a masters course at the University of Pennsylvania that teaches students to use Python to gather, visualize, and analyze geospatial data with an urban planning and public policy focus.
Contact Info
nicholas.adam.hand@gmail.com
Philadelphia, PA