San Francisco Bay Area
I'm a builder by disposition, happiest once I've solved a problem and then built the thing that keeps it solved. My family and I traded Texas for the Bay Area not long ago; most evenings I'm cooking dinner, most mornings I'm on a trail or in open water, and there's almost always a Raspberry Pi in the next room doing something it wasn't strictly asked to.
Career
I notice patterns. It's less a skill than the thing my mind does on its own, and for a long time it was just how I made decisions, a quiet habit running in the background. Then a high school statistics class gave the habit a name and a method: the same teacher who'd walked me through algebra and geometry handed me statistics, and the patterns I'd been sensing became things I could quantify, test, and use to predict what came next. The instinct had turned into a discipline.
Statistics gave me the framework; programming gave it reach. Data science was where the two met, the place where statistical thinking, code, and real business context could be pointed at questions that didn't have clean answers. That's the work I kept choosing: not the tidy problems but the messy ones, where the data was incomplete, the requirements moved, and the right answer had to be built rather than looked up.
Fifteen years later, that's still the thread. I've built fraud models in consumer lending, written data governance rules at telecom scale, and shipped risk models that steered infrastructure decisions worth millions. Now, at HFD, it's the credit risk scorecards and loss projections that keep a lending portfolio honest. The domains kept changing; the way of thinking didn't. Somewhere in there it hardened into a conviction I co-authored a paper about in 2018: that data about people belongs to those people, and that the models we build on it should be able to explain themselves. It's why I care as much about whether a model is governed and trustworthy as whether it's accurate, and why, off the clock, everything I build runs on hardware I own.
Focus
M.S. in Data Science, Southern Methodist University, 2018
B.S. in Statistics, University of Texas at Dallas, 2009
Selected work
Portfolio analytics
Python · Streamlit · self-hosted
One honest view of a portfolio scattered across three custodians, with no third-party aggregator.
ML budgeter
Naive Bayes · in-browser
A classifier that auto-categorizes transactions and flags the ones it's unsure about.
Home lab
Raspberry Pi · Docker · Tailscale
A private, containerized stack that runs the household's services on hardware I own.
E-ink family calendar
Raspberry Pi · E-ink · in progress
A wall-mounted display that keeps the whole family organized on one glanceable page.
Remote caregiving tool
FastAPI · Tailscale · PWA
Low-friction medication logging and tiered alerts for a relative a few hundred miles away.
Home lab & self-hosted services
Raspberry Pi 4 · Docker
Own the household's digital infrastructure: privacy, control, and no monthly rent to third-party cloud services.
A containerized stack on a Raspberry Pi 4: network-wide DNS filtering (Pi-hole + Unbound), zero-trust remote access with no open ports (Tailscale), version control (Gitea), a Samba NAS, home automation (Home Assistant), and a private Nextcloud, all hardened over SSH.
A private, resilient stack reachable from anywhere without exposing a single port, and a Nextcloud that retired ~400 GB of paid cloud storage.
E-ink family calendar
Raspberry Pi · E-ink · in progress
Give the whole family one calm, glanceable view of everything that matters, so we're all on the same page without another app to check.
A wall-mounted e-ink display driven by a Raspberry Pi, pulling calendar and weather feeds into a single layout: birthdays and anniversaries, vacations, school functions and homework, and the odd special occasion.
In progress. The e-ink panel keeps it always on and easy on the eyes, and I'm still waiting on hardware.
Remote caregiving tool
FastAPI · Tailscale
Support a relative who lives a few hundred miles away, with reliable medication logging and escalation and no friction for the person using it.
A progressive web app (FastAPI + SQLite) with near-frictionless logging, a YAML-driven schedule, and tiered alerts over a self-hosted notification stack, reachable securely over Tailscale.
Dependable remote logging with escalation when something's missed, private and entirely on infrastructure I control.
Personal
Most of my time off is outdoors with my two daughters. I'm often on the trails either running or hiking with my daugghters and we swim open water whenever the water cooperates. I cook most nights too, though "cook" may overstate it; my daughter maintains it beats takeout, and I've decided to take her at her word.
I'm partial to a well-made tool. Fountain pens are the obvious one, and the reason there's iron gall blue-black running through this whole page. The less obvious one is my Wüsthof chef's knife, which does most of the real work behind that dinner framework. Both come down to the same small pleasure: something built with care, kept sharp, doing exactly what it's for.
Contact
Find me on LinkedIn, or write to cc at cynthiacarolina dot com.
Colophon
corDeHierro: an iron heart. Hierro is iron, the ink is iron gall, the φ is the nib it's written with. Written by hand in HTML and CSS, with no framework, no build step, no analytics, no trackers, and nothing loaded from anyone else's server. Set in Iowan Old Style with a monospace counterpoint, iron gall blue-black on laid paper, inverted after dark. One file, about 28 KB.