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Jose Paulo De Sousa Lima - Senior CRE Analyst

Location: Lisbon, Portugal

Compensation range discussed: $1,900 - $2,300

LinkedIn Profile | email: josepvslima@outlook.com | Phone: +351 910 380 690

Schedule Availability (EST): available for a schedule commitment of 50 hours/per week. Exact shift TBD with the hiring company

Summary

Financial Analyst with over 1.5 years of experience managing liquid assets and corporate real estate for a multi-family office at Astron Wealth Management. He regularly coordinates with the Morgan Stanley private banking office in Miami and supports management headquartered in Texas, overseeing US market accounts and financial transactions. His direct commercial real estate expertise includes managing corporate building funds, calculating cap rates, monitoring default risk, and developing operational strategies to reduce vacancy rates. He integrates strong analytical capabilities with visual design, using Python, Excel, and AI tools (e.g., Gemini, ChatGPT) to automate complex financial models and consolidate data. Furthermore, he leverages Canva and PowerPoint to translate these analytical insights into polished corporate presentations, providing him with the precise technical and aesthetic foundation required to execute sophisticated real estate marketing deliverables.

Meet Jose Paulo

This video from our screening interview provides a look into José Paulo's background and experience:

Candidate Snapshot

US-based Experience

• Texas-Led Operations: Reports directly to US-based management in Texas, executing operations for a multi-family office that oversees ~$170M in liquid assets and ~$70M in real estate holdings globally.

• US Institutional B2B Interaction: Collaborates frequently with the private banking divisions of Morgan Stanley and Wells Fargo in Miami to monitor client accounts, evaluate bond-switching opportunities, and manage offshore transactions.

Commercial Real Estate Expertise

• Corporate Asset Operations: Actively manages corporate buildings in São Paulo for a client's Real Estate Investment Trust (REIT). Evaluates property sales by comparing expected versus actual cap rates to ensure profitability.

• Property-Level Management & Repositioning: Analyzes operational elements to appreciate underperforming properties. Strategizes directly on tenant retention and building management to maintain low vacancy rates and prepare assets for future profitable sales.

• Private Equity & Development: Serves as Vice President and Head of Real Estate for the Lisbon Investment Society, currently leading a private equity feasibility project focused on developing a data center in the Iberian Peninsula.

Real Estate Documentation Development

• Valuation & Deal Material Inputs: Routinely structures financial models (DCF, DDM, Monte Carlo simulations) and conducts macro-market studies that serve as the quantitative foundation for deal-related materials.

• Corporate Presentation Design: Designed the standardized visual templates currently used by the Lisbon Investment Society. Applies advanced proficiency in Canva and PowerPoint to ensure marketing materials and financial reports maintain strict aesthetic and corporate standards.

Education

• Bachelor’s Degree in Business Management | ISEG - Lisbon School of Economics & Management (2026)

• Coursework in Portfolio Construction and Analysis with Python | EDHEC Business School

Tools & Technologies

• Data & Financial Modeling: Advanced Python, Microsoft Excel, Power BI.

• Design & Presentation: Canva, Microsoft PowerPoint.

• AI Technologies: Gemini, Claude, ChatGPT, Perplexity, Nano Banana (utilized for coding, visual generation, and financial data interpretation).

Key Qualifications & Highlights

• Advanced AI Integration & Workflow Automation: Displays strong technical resourcefulness in solving operational bottlenecks. Upon identifying structural inaccuracies in a family office's manual portfolio rebalancing process, he independently developed a custom Python-based solution to automate the calculations. This initiative entirely replaced the legacy Excel system, mitigating human error and drastically optimizing monthly processing time.

• Complex Financial Modeling Capabilities: Built an automated, AI-driven model for fixed-income bond switching and forward break-even analysis. This high-level capability in programming and Monte Carlo simulations provides a rigorous, highly accurate analytical backbone for commercial real estate underwriting and investment analysis.

• Cross-Functional Design & Data Translation: Seamlessly bridges the gap between back-office financial modeling and front-office deliverables. Combines raw data processing skills with an inherent focus on visual design, transforming complex macroeconomic parameters into polished, investor-ready presentations.

• Global Acumen & Multilingual Proficiency: Operates fluently across international markets, holding C1 certifications in both English and Spanish. Effectively navigates cross-border transactions by supporting US-headquartered management, coordinating with Miami-based banking partners, and overseeing real estate assets in Latin America while residing in Portugal.

• Leadership in Academic Investment Communities: Directs operations for the largest investment association in Portugal (comprising 130+ members across 20 nationalities) as Vice President. Manages cross-functional teams spanning real estate, quantitative finance, and equity research, demonstrating strong organizational alignment and project management skills.

Screening Interview - Key observations

• Unpublished CRE Research: He is currently conducting independent research on commercial real estate market multiples across the Iberian Peninsula, culminating in an unpublished paper.

• Task Preferences & Workflow Automation: He thrives when combining real estate analytics with advanced technology to eliminate repetitive administrative work. He explicitly stated a strong preference for utilizing AI platforms (such as Claude and Perplexity) to engineer automated workflows, allowing him to focus on complex financial modeling rather than manual data entry.

• Areas for Improvement: He currently lacks native familiarity with standard US Commercial Real Estate marketing terminologies (such as Offering Memorandums and Loan Packages). Additionally, he expressed a strong distaste for manual data-tracking tasks—which he currently performs due to the lack of public transaction pricing in the Brazilian market—and prefers environments where data availability readily enables automation.

• Adaptability & Upward Management: Demonstrated a strategic approach to stakeholder buy-in and process improvement. When implementing his Python automation for portfolio rebalancing, he navigated resistance from senior leadership by first mastering the legacy Excel system to build credibility. Furthermore, he displayed high adaptability by independently researching unfamiliar US real estate terminology prior to the interview, successfully correlating those concepts with his existing corporate real estate operations.