001 / PYTHON PACKAGE↗
TEMPORAL COMPUTING
dately.
A public Python library I built. Standardize invoice dates, reporting periods and calendar expressions—then see the result feed a live cash-forecast example.
001 / SECOND DIMENSION © CJ MOORE — BUILT, NOT BOUGHT
● HELLO, OTHER SIDE OF MY BRAIN
I make
complexity
compute.
I'm C.J. A finance strategist who codes, builds data platforms, trains models, and obsessively removes the distance between information and action.
PYTHON / SQL / MACHINE LEARNING / SYSTEMS DESIGN✺
[ 75 SIGNAL NODES / ACTIVE ]SYSTEM 02.0FIG. A / SIGNAL FIELDMODEL / ACTIVE
DATA
→
DECISION
→
DECISION
0x01 DATA INGESTION
0x02 MODEL INTELLIGENCE
0x03 DECISION SYSTEMS
++DATA ENGINEERING ✳ MACHINE LEARNING ✳ FINANCIAL SYSTEMS ✳ PYTHON LIBRARIES ✳ MODEL GOVERNANCE ✳ ANALYTICS PLATFORMS ✳
01 // OPEN SOURCETools I built.
Tools I built.
For the work finance does.
Python libraries I built and published for anyone to use—from cleaning financial inputs to automating reporting and analyzing market data. Choose a library to try it live, explore the code, or install it.
002 / PYTHON PACKAGE↗
DATA NORMALIZATION
numbr.
A public Python library I built. Normalize number formats in payment terms, budget assumptions and period labels—then see the result feed a live finance example.
003 / SUPPORTING LIBRARY↗
AUTOMATED REPORTING
azauthlib.
Helps automated finance reports and data workflows connect to Microsoft services with fewer repeated sign-ins. Built on MSAL, with encrypted token caching and OS credential storage to help keep client secrets out of scripts.
004 / PYTHON PACKAGE↗
FINANCIAL DATA / PYTHON LIBRARY
quantsumore.
A Python library for financial data and analysis. This live demo showcases its technical-analysis module with nine indicators, configurable windows and inspectable calculations.
REAL REPOSITORIES. REAL CODE.VIEW COMPLETE GITHUB PROFILE ↗
02 // APPLIED ENGINEERINGNot just models.
Not just models.
Systems that survive.
Patterns I've applied in enterprise finance and analytics environments, where accuracy, resilience and stakeholder trust matter as much as clever algorithms.
01 / DATA
One trusted data layer.
Normalize fragmented ERP, CRM, billing and operating data into governed models that let decision-makers ask better questions without arguing over definitions.
02 / INTELLIGENCE
Forecasts with a feedback loop.
Connect time-series and machine-learning models to business drivers. Validate accuracy, explain assumptions, monitor drift, then deliver the outputs where people make decisions.
03 / TRUST
Built to be believed.
Data lineage, reconciliations, repeatable testing and exception monitoring turn automated analytics into defensible management reporting.
Enterprise systems are described at a high level. Visuals are original illustrations; no private datasets, architecture diagrams or source code are disclosed.
03 // TALK TO THE SYSTEMGo ahead.
Go ahead.
Type something.
Curious where to go next? A small browser-only command console will help you navigate the portfolio. Try help, projects, stack or finance.
C.J. Moore / systems interface v1.0
Welcome to the other side. Type help to begin.
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QUICK COMMANDS
04 // OPEN CHANNELHave a problem
Have a problem
worth solving?
Strategic finance problem, data problem, or a little of both—those are my favorite conversations.