Data Analyst

Company Description Raiven Commercial Real Estate is a growth-focused firm specializing in data-informed investment and asset management decisions. The company leverages market research, financial analysis, and technology to optimize portfolio performance and identify new opportunities. Team members collaborate across disciplines to deliver insights that support clients’ strategic real estate goals. Raiven values analytical thinking, integrity, and a commitment to continuous improvement in a fast-paced commercial real estate environment.Role Description The Data Analyst role at Raiven Commercial Real Estate is full-time. In this role, the Data Analyst gathers, cleans, and analyzes real estate and financial datasets to support investment decisions, portfolio management, and market forecasting. Daily tasks include building dashboards and reports, performing statistical analyses, and developing data models that highlight trends, risks, and opportunities. The Data Analyst collaborates with asset managers, acquisition teams, and leadership to present findings in clear visual and written formats. The role also involves maintaining data quality, documenting methodologies, and recommending improvements to analytics workflows and tools.QualificationsStrong analytical skills with experience in data analytics and data modeling.Solid foundation in statistics, including descriptive and inferential methods relevant to business and market analysis.Effective communication skills, with the ability to translate complex data into clear, actionable insights for non-technical stakeholders.Proficiency with data tools such as Excel, SQL, and business intelligence platforms (e.g., Power BI, Tableau, or similar).Bachelor’s degree in Data Science, Statistics, Economics, Finance, Computer Science, or a related field, or equivalent practical experience.Attention to detail, strong organizational skills, and the ability to manage multiple projects and deadlines.Experience working with real estate, financial, or market data is beneficial.