Data Analyst

Position: Data Analyst (Real Estate)

Location: London

Salary: Up to £70,000 per annum + bonus + benefits

Position Overview

The Data Analyst will support the Investment team by managing, analysing, and abstracting data from real estate transactions and agreements. This role requires expertise in data abstraction, data management, and a strong understanding of market trends within the real estate industry. The Data Analyst will be responsible for transforming complex contract data into actionable insights, delivering trend and forecast reports, and supporting data-driven decision-making across the investment portfolio.

Key Responsibilities

1. Data Abstraction and Documentation Analysis
   • Review & Abstract Documentation: Analyse a range of real estate documents, including Purchase and Sale Agreements (PSAs), Closing Statements, Development Agreements, Amendments, and Options, to extract key terms, obligations, milestones, and financial commitments.
   • Populate Abstraction Templates: Manually input critical data points, such as contract terms, deadlines, and financial obligations, into standardized templates for effective record-keeping and compliance tracking.
   • Manage Obligations and Key Dates: Systematically document and track ongoing obligations, including renewal dates, option deadlines, and development milestones, ensuring these are accurately reflected in the system for proactive management.
2. Market Trends Analysis and Forecasting
   • Market Data Collection and Analysis: Collect and analyse data on real estate market trends, economic indicators, and comparable transactions to inform the Investment team of current market conditions and potential impacts on portfolio assets.
   • Forecasting Models: Develop forecasting models to predict real estate market trends, rental rates, occupancy levels, and property valuations. Apply statistical and machine learning techniques to provide predictive insights for portfolio strategy.
   • Strategic Insights: Prepare and present periodic trend and forecasting reports that highlight opportunities and risks based on shifting market conditions, aiding in strategic decision-making for acquisitions, dispositions, and asset management.
   • Benchmarking and KPI Analysis: Conduct benchmarking against industry standards and relevant KPIs, providing actionable insights to improve investment strategies and optimize portfolio performance.
3. Data Management and System of Record Entry
   • Data Entry: Enter and maintain accurate data on 3rd-party agreements, infrastructure information, and project timelines within the system of record.
   • Database Integrity and Clean-up: Support ongoing data clean-up initiatives to enhance the completeness and reliability of historical data.
   • Cross-Verification and Quality Control: Regularly cross-check data entries, review peers' data for accuracy, and ensure alignment with data quality standards.
4. Reporting and Portfolio Analytics
   • Performance Reporting: Generate and deliver regular portfolio reports on metrics such as occupancy rates, asset value trends, and key performance indicators for senior management.
   • Ad-Hoc Analytics and Visualization: Produce ad-hoc analysis and data visualizations (using tools like Power BI, Tableau) to answer specific questions from the Investment team, transforming complex data into accessible insights.
   • Market and Portfolio Metrics Tracking: Develop and track portfolio-level metrics, including investment yield, market growth rates, and economic conditions, and compare these against portfolio performance to guide strategic initiatives.
5. Collaboration and Process Improvement
   • Engage with Investment and Legal Teams: Collaborate with internal stakeholders to interpret and standardize data abstraction processes for consistency and accuracy.
   • Enhance Data Abstraction Processes: Identify and implement opportunities to streamline data abstraction and entry, improving efficiency and data quality.
   • Mentorship and Knowledge Sharing: Support the development of the Investment team by training team members on data abstraction techniques, data entry protocols, and market analytics methodologies.

Qualifications and Skills

Required:

• Educational Background: Bachelor's, Master's or PhD degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Econometrics, or a related field.
• Real Estate Knowledge: Strong understanding of real estate investment fundamentals, sales transactions, and market trends.
• Analytical Skills: Proficiency in data analysis and forecasting models, with demonstrated experience in extracting actionable insights from complex data sets.
• Detail-Oriented: Exceptional attention to detail, especially when abstracting data from contracts and documents.
• Technical Skills: Skilled in data management and analytics tools (e.g., Excel, SQL, Python, R) and data visualization platforms (e.g., Power BI, Tableau).
• Communication Skills: Strong written and verbal communication skills, with the ability to convey complex analytical insights in a clear, actionable format.

Preferred:

• Experience in Real Estate Analytics: Previous experience in real estate investment, market analysis, or portfolio management.
• Advanced Forecasting Techniques: Experience in predictive analytics, market trend modeling, or economic forecasting.
• Familiarity with Real Estate Legal Documentation: Ability to interpret contractual language and obligations in real estate agreements, particularly as it pertains to financial and development obligations.

If you are interested in this exciting opportunity to join a leading, international real estate investment fund, please contact Sam Lee on 020 3757 5000 or email s.lee@capstone-recruitment.com