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Rafaela Bayas - Senior CRE Underwriting Analyst

Location: Quito, Ecuador

Compensation range discussed: $1,900 - $2,300 USD/month

LinkedIn Profile | Email: rafabayas@hotmail.com

Earliest date she can join the company: Immediately

Quick Recruiter Note: The candidate expressed a preference for a vacation policy of 15 days, an increase from the 10 days listed in the job description.

Summary

Real Estate Investments Sr. Analyst Graduated from the University of North Carolina at Chapel Hill with a B.A. in Economics and Public Policy and a Master’s in International Development from The University of Edinburgh, she has 3 years of real estate experience primarily with Greystar in both the US and UK markets. Her expertise lies in building complex financial models from scratch in Excel for both development and investment underwriting. She has underwritten multifamily and mixed-use assets, gaining exposure to retail and office components. While based in the US, she held an oversight role reviewing an average of five underwriting models per week from teams across major markets, including the Northeast, the Carolinas, the West Coast, and the Chicago MSA. She is experienced in analyzing financial statements like T-12s and operating statements to model complex cash flow waterfalls and run sensitivity analyses.

Meet Rafaela

This video from our screening interview provides a look into Rafaela's background and experience.

Candidate Snapshot

US-based Real Estate Experience

• Direct US Market Roles: Has 1 year of experience working in the US (Charleston, SC and Charlotte, NC) for top-tier firms.
• National Exposure: While based in Charleston with Greystar, held a national oversight role reviewing underwriting models from teams across the Northeast (New York, Boston), the West Coast (Los Angeles, San Francisco), the Carolinas, and the Chicago MSA.
• Firms: Gained experience with Greystar, a global leader in rental housing, and Asana Partners, a retail real estate investment company.

Asset Classes

• Multifamily & Mixed-Use: Her primary expertise lies in underwriting residential and complex mixed-use assets.
• Retail & Office: Gained exposure to underwriting retail properties during an internship with Asana Partners and through the analysis of retail and office components within mixed-use developments at Greystar.

Underwriting Skills & Experience

• Buy-Side Focus: Experience is primarily on the buy-side, underwriting assets for acquisition and long-term hold, but also includes analysis for the sell-side.
• Quality Control & Oversight: In her Operations Analyst role, she was responsible for reviewing and assessing the feasibility of development opportunities by auditing an average of five underwriting models per week from teams across the United States, ensuring the accuracy of assumptions before Investment Committee review.
• Full-Cycle Analysis: Her process includes analyzing T-12s, rent rolls, and operating statements to model complex cash flow waterfalls, equity structures, and run sensitivity analyses to maximize IRR or target a specific NOI.

Financial Modeling Expertise

• Advanced Excel: Proficient in building and manipulating complex financial models entirely within Excel.
• From Scratch & Template-Based: Has direct experience building underwriting models from scratch for development and investment opportunities in the UK. In the US, she focused on adapting and tweaking complex base models for specific deal structures and asset phases.
• Scope: Creates models for both development and investment scenarios, calculating key metrics such as IRR, Cap Rates, and NOI, and running various sensitivity analyses.

Education

• MSc International Development | The University of Edinburgh (2025)
• B.A. Economics and Public Policy | University of North Carolina at Chapel Hill (2021)

Tools Used

• Financial & Data: Excel (Advanced), Stata, CoStar, Yardi.
• Programming: Python (Basic).

Key Qualifications & Highlights

• The "Validator" Profile: Her experience at Greystar in the US was not just about building models, but acting as a strategic gatekeeper. Her core responsibility was "revising an average of five different underwriting models per week," a high-volume quality control function that has trained her to quickly identify errors, weak assumptions, and financial inaccuracies, a critical skill for ensuring the reliability of an AI-driven underwriting platform.
• Cross-Border Complexity: She successfully transitioned between the US and UK markets, demonstrating high adaptability. In London, she was responsible for the budget management of a ~£1B development masterplan and operated in a hybrid role between the development and investment teams, proving her ability to manage large-scale financial data in complex, multi-phased projects.
• Entrepreneurial Problem-Solver: She describes herself as an "entrepreneur" within the workforce considering herself highly independent and resourceful. When tasked with managing the legal negotiation for over 30 consultant contracts in London—a process she was unfamiliar with—she proactively sought guidance from other internal teams to understand the process and meet her deadline, all without needing to escalate to her direct managers.
• US Academic & Professional Fluency: With a degree from the University of North Carolina at Chapel Hill and professional experience in both North and South Carolina, she has a native-level command of English and a deep, practical understanding of US business culture and commercial real estate terminology.

Screening Interview - Key Observations

• Entrepreneurial & Proactive Problem-Solver: Identifies her core strength not just as a technical skill, but as having an "entrepreneurial" mindset within the workforce. She demonstrated this by proactively taking on the legal negotiation for consultant contracts in London, a task she was unfamiliar with. Instead of escalating to her busy managers, she independently sought out another internal team for guidance, learned their process, and successfully met her deadline.
• Strategic Prioritization Under Pressure: When faced with conflicting priorities, she manages her workload by setting "self-deadlines." She works backward from the final due date, factoring in the time her managers need for review, ensuring she delivers her work earlier. This allows for a collaborative review process without creating last-minute emergencies.
• AI Curiosity and Practical Application: While she has not used AI for underwriting, she uses Gemini to streamline processes and ChatGPT for research and writing. She expressed genuine curiosity and excitement about the prospect of an AI-native tool for underwriting, indicating a strong interest in the company's core product.
• Self-Aware & Coachable: Acknowledges her primary weakness is the one-year gap since her last full-time real estate underwriting role. She has a clear plan to mitigate this by independently sharpening her skills before starting a new position to ensure she is fully prepared from day one.
• Insightful Inquirer: Rather than asking standard questions about the company, her primary question was about her own potential "weak spots" for the role and what she could be working on for the next stages of the interview process. This demonstrates a high degree of self-awareness and a proactive desire for professional growth.