Jobs and Careers

Business Analyst, Real Estate Data Strategy

San Diego, United Statesfull_timeVerifiedPosted 19 May 2025

About the role

Realty Income aims to be a globally recognized leader in the S&P 100, committed to creating long-term value for all stakeholders. These stakeholders include our dedicated team members, who embody our purpose: building enduring relationships and brighter financial futures. This guiding principle serves as a beacon for our team, influencing every action we take. Realty Income’s employees consistently invest their time, commitment, and dedication into the company, and in turn, they receive investment returns in the form of purpose, belonging, and opportunities for advancement. Realty Income is committed to best-in-class corporate responsibility practices through environmental initiatives, governance programs, and community outreach projects. From the boardroom to the breakroom, our team members make a difference every day. Position OverviewThis hybrid role (Tuesday, Wednesday, and Thursday on-site) offers a unique opportunity to apply predictive analytics and advanced data modeling to strategic real estate decision-making. As the Analyst, Business Insights & Analytics (Real Estate Data Strategy), you’ll work across departments—including Acquisitions, Asset Management, Development, Legal, and Tenant Credit—to uncover insights that shape our portfolio, reduce risk, and improve operational efficiency.You’ll go beyond traditional business intelligence to develop forecasting models, assess risk in investment decisions, and support the evolution of data analytics into a core capability at Realty Income. Over time, this role is designed to evolve into a leadership opportunity as we continue to expand our analytics team and capabilities globally.Key ResponsibilitiesCollaborate & Strategize

Partner with business leaders and stakeholders across departments to understand challenges and uncover data-driven solutions.
Identify and triage data issues, inconsistencies, and opportunities for improvement.
Communicate complex data concepts clearly to both technical and non-technical audiences.
Propose and implement scalable analytics frameworks and best practices.

Analyze & Forecast

Apply predictive analytics to real estate cash flow modeling and investment case development.
Use Excel, SQL, and other tools to transform structured and unstructured data into insights.
Design scenario analyses that support cross-functional teams in evaluating risk and opportunity.
Ensure data pipelines and analytical models are accurate, timely, and actionable.

Visualize & Recommend

Develop dashboards and executive-ready reports that communicate KPIs and strategic trends.
Partner with technical teams to build intuitive visualizations using Power BI, Tableau, or Looker.
Monitor and refine reporting deliverables as business needs evolve.

Innovate & Build

Contribute to the design and development of machine learning models and AI solutions.
Collaborate with technical teams on model selection, feature engineering, and statistical testing.
Stay informed on the latest in analytics, ML/AI, data architecture, and industry tools.

Qualifications:A qualified candidate is typically expected to have:

Bachelor’s degree in a relevant field (e.g., MIS, Finance, Computer Science, Statistics, or related).
Internship or professional experience in business analysis, analytics, consulting, or business intelligence.
Strong foundation in Excel for financial modeling and data analysis.
Basic proficiency in SQL and a willingness to grow technical skills.
Ability to synthesize complex information into insights and communicate clearly.
Familiarity with data visualization platforms (e.g., Power BI, Tableau, or Looker).
Solid understanding of statistics, probability, and risk assessment principles.
Collaborative mindset with a drive to take initiative and lead in ambiguous situations.

Preferred:

Master’s degree in a quantitative or technical field.
Exposure to predictive modeling, machine learning, or AI applications.
Experience working with real estate analytics, investment modeling, or risk assessment.
Understanding of data architecture and working knowledge of cloud-based platforms (e.g., Snowflake, BigQuery, AWS, or Azure).