Acquisition Underwriting
Price, income, expenses, debt, returns, and exit — modeled with the sensitivities that show where the deal really stands.
I help investors, operators, and real estate teams evaluate opportunities, understand performance, and improve reporting through property analysis, financial modeling, market research, and business intelligence. The work turns complex information into clear, structured findings that can be reviewed, challenged, and acted on.
Whether the work involves a deal, a model, a market, a portfolio, or a reporting system, the purpose is the same: organize the information, identify what matters, surface risks and performance drivers, and make the next decision or action clearer.
A practical combination of real estate analysis, financial judgment, data skills, and systems thinking.
The real estate and analytical disciplines I bring together to evaluate opportunities, understand performance, and support better decisions.
Price, income, expenses, debt, returns, and exit — modeled with the sensitivities that show where the deal really stands.
Structured, auditable models for acquisitions, development, debt, and operations, with every figure traceable to its source.
Comps, demographics, access, supply, and demand translated into evidence that confirms — or challenges — the story.
NOI, occupancy, rent, expenses, variance, and coverage tracked across properties so performance does not drift unnoticed.
Stress the assumptions, compare alternatives, and identify the breakpoints where the investment answer changes.
Complex analysis distilled into a clear summary, dashboard, or memo for owners, investors, partners, and teams.
Core capabilities used across deal analysis, ongoing performance work, and client-facing decision support.
Cash flow analysis · Pro forma development · Returns analysis · Debt sizing · Valuation · Variance analysis
Underwriting · Due diligence support · Rent and sales comps · Market research · Location analysis · Portfolio review
Data cleaning · KPI design · Dashboard development · Management reporting · Scenario modeling · Executive summaries
The platforms I use to build models, analyze data, automate workflows, and produce clear, decision-ready outputs.
Eight years of experience spanning financial reporting, market research, business operations, data management, and real estate investment analysis.

I’m Angelica, a Real Estate Analyst working across property analysis, financial reporting, market research, and business intelligence. I organize property, market, financial, and operational data into structured models, reporting systems, and clear findings that help evaluate opportunities and understand performance.
A background in financial management, business operations, and data analysis allows me to connect technical detail with commercial context, clarifying not only what the numbers show but what they mean for the decision at hand.
A collection of platforms, analytical projects, and case studies.
A 244-property short-term rental expansion analysis — normalized rent modeling, nightly-rate optimization, and property-level cash flow feeding a disciplined capital-allocation call, with an interactive Tableau sensitivity dashboard.
An interactive ten-year acquisition pro forma for a 50,000 SF Philadelphia retail center — levered and unlevered returns, credit metrics, and a live rent-growth / exit-cap sensitivity matrix.
An interactive monthly development pro forma for an 85,000 SF San Francisco build-to-suit — construction financing, refinance cash-out, and levered / unlevered returns in a live, editable model.
Reconstructed full financial statements from 153,000+ raw transactions for a multi-stream retail business — uncovering $22,415 in shrinkage and delivering a data-driven expand-or-sell recommendation backed by a 2.65× DSCR.
A modular Python/Jupyter pipeline that automates business review reporting from fragmented data sources — turning newsletter, sales, and website analytics into executive-ready weekly, monthly, and quarterly reports.
Formal training in financial management, accounting, economics, and business strategy supports the analytical work presented throughout this portfolio.
Credentials across real estate, finance, data analytics, technology, and business.
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Applied Data Science Capstone
Data Analyst Capstone Project
Data Management Professional Certificate (V2)
IBM Business Intelligence (BI) Analyst Professional Certificate (V3)
IBM Data Analyst Professional Certificate (V3)
IBM Data Science Professional Certificate (V3)
AI Foundations for Everyone Specialization
Applied Data Science Specialization (V3)
Data Analysis with Python
Data Science Fundamentals Specialization (V3)
Data Visualization with Python
Excel Essentials for Data Analytics
Generative AI Essentials for Data Analytics
Generative AI Essentials for Data Science
Generative AI for Data Analysts Specialization
Generative AI for Data Scientists Specialization
Introduction to Data Science Specialization (V2)
Machine Learning with Python (V2)
Python for Data Science and AI
Business Intelligence Essentials
Data Analysis & Visualization Foundations Specialization (V3)
Data Analytics Essentials
Data Engineering Essentials
Fundamentals of Business Analysis
Meta Data Analyst Professional Certificate
Microsoft 365 Fundamentals Specialization(v.1)
Project Management Essentials
Statistics for Data Science with Python
Google Advanced Data Analytics Certificate
Google AI Essentials V1
Google Business Intelligence Certificate
Google Data Analytics Professional Certificate (v2)
Google Digital Marketing and E-Commerce Professional Certificate
Google IT Automation with Python Professional Certificate
Google Project Management Professional Certificate (v2)
Google Prompting Essentials
Google/University of Illinois' Gies College of Business Dual Credential
Engagements can cover a property or portfolio, a defined modeling or reporting project, or ongoing analytical support for a real estate team.
Evaluation of purchase assumptions, property operations, debt, returns, exit, and downside exposure.
New models, model rebuilds, assumption audits, formula checks, scenario design, and decision-ready summaries.
Comparable evidence, demographics, supply and demand, access, risks, and market context for an investment thesis.
Operating performance, NOI, occupancy, rent, expense, variance, and portfolio-level KPI analysis.
Management dashboards, executive summaries, investment memos, and clear reporting for owners, partners, and internal teams.
Connected spreadsheets, trackers, workflow automations, and repeatable reporting systems that reduce manual work.
Practical answers about project fit, scope, fees, timelines, confidentiality, and how engagements are structured.
Projects involving acquisition underwriting, financial modeling, market and location research, property or portfolio performance analysis, dashboards, and analytical systems are the strongest fit. The work is most effective when there is a defined property, decision, dataset, or reporting need.
Yes. I can review, rebuild, document, or extend existing Excel or Google Sheets models, dashboards, trackers, and reporting workflows. The scope depends on the condition of the existing file and what it needs to support.
Property files, operating data, models, investor materials, and internal business information are treated as confidential. I can work under a client-provided NDA and follow your organization’s access and file-handling requirements.
A short overview of the property or business question, the decision you need to make, the desired timing, and a general description of any existing files or data. There is no need to send confidential materials before the scope and handling requirements are agreed.
Yes. Work can be structured as a fixed-scope project, a short analytical sprint, or ongoing analytical support. The right arrangement depends on the scope, volume of work, expected turnaround, and whether support is needed once or on a recurring basis.
Scope, fees, and timelines depend on the project’s requirements, complexity, available information, and desired turnaround. If there is a mutual fit and both parties decide to proceed, the agreed deliverables and terms are documented before any analytical work begins.
Schedule a brief introductory call or send an email to discuss your project, timeline, and whether the engagement is a good fit. Scope, deliverables, and fees are agreed before any analytical work begins.