Sr. Real Estate Financial Data Analyst

Description

The Role:

The Senior Real Estate Financial Data Analyst will lead business intelligence, analytics, reporting, and decision-support for a growing self-storage and real estate organization. Reporting to the Chief Financial Officer, this hands-on role transforms financial, operational, customer, and market data into actionable insights that improve revenue, occupancy, budgeting, forecasting, customer service, and portfolio performance. The successful candidate will be:

• Highly organized, detail-oriented, and able to connect analysis to the broader business strategy.

• Proactive, resourceful, and comfortable working independently in a fast-paced environment.

• Customer-service focused and responsive to the needs of executives, corporate teams, and field operations.

• A practical problem solver who communicates complex findings clearly to non-technical stakeholders.

• Collaborative, adaptable, accountable, and willing to work on-site in York, Pennsylvania.

Essential Duties:

Specific duties and functions of the position include, but are not limited to:

• Business Intelligence and Power BI:

o Serve as the company’s Power BI subject-matter expert; design, develop, deploy, and maintain executive, financial, operational, revenue-management, marketing, and property-level dashboards.

o Build scalable data models using Power Query, DAX, semantic modeling, automated refreshes, permissions, documentation, and quality controls.

o Replace manual spreadsheet reporting with accurate, repeatable, user-friendly reporting solutions and train employees to interpret and use the information.

• Self-Storage, Revenue Management, and Customer Analytics:

o Analyze occupancy, economic occupancy, move-ins, move-outs, achieved and street rates, discounts, concessions, delinquency, retention, lead conversion, and unit-type performance.

o Partner with operations and revenue management to evaluate pricing, rate increases, promotions, demand patterns, customer behavior, competitive conditions, and underperforming properties.

o Measure the impact of operational, marketing, pricing, and customer-service initiatives and identify opportunities to improve revenue, occupancy, retention, and net operating income.

• Budgeting, Forecasting, and Financial Analysis:

o Support annual property and portfolio budgets, monthly forecasting, variance analysis, scenario planning, and performance comparisons to budget, prior year, forecast, and underwriting.

o Analyze revenue, operating expenses, NOI, capital expenditures, and other financial measures; clearly explain significant variances and business implications.

o Assist with acquisition underwriting, due diligence, post-closing performance tracking, and integration reporting as requested.

• Data Science, Automation, and Systems Integration:

o Develop statistical, predictive, machine-learning, or AI-supported models when appropriate for revenue forecasting, pricing optimization, customer retention, lead conversion, and property performance.

o Develop, maintain, or support APIs and other integrations among operational, accounting, accounts-payable, revenue-management, and reporting platforms.

o Create reliable data pipelines and automated workflows that consolidate information, reduce duplicate entry, and eliminate unnecessary manual processes.

o Evaluate emerging analytical and AI technologies based on business value, scalability, cost, security, and user adoption.

• Data Governance, Quality, and Collaboration:

o Establish consistent KPI definitions, reconcile outputs to source systems and accounting records, troubleshoot discrepancies, and maintain documentation of data sources and methodologies.

o Protect confidential company, customer, employee, and financial information and support sound data-governance practices.

o Translate business questions into practical analytical solutions, manage competing priorities, and provide responsive service to internal customers and third-party technology partners.

Requirements

Experience and Qualifications:

We’re looking for someone with the following:

• Bachelor’s degree in data analytics, data science, statistics, mathematics, computer science, finance, accounting, economics, business, or a related field.

• Five or more years of progressively responsible experience in business intelligence, analytics, financial analysis, data science, or a comparable role.

• Expert-level Power BI experience, including dashboard design, DAX, Power Query, data modeling, visualization, administration, and automated reporting.

• Self-storage experience strongly preferred, including property operations, budgeting, revenue management, pricing, occupancy, and multi-location performance analysis.

• Advanced Excel skills; working knowledge of SQL, relational databases, and integration of data from multiple platforms.

• Experience with API development or integration. Python, R, Microsoft Fabric, Azure, data warehouses, machine learning, or AI tools are additional advantages.

• Experience with Sage 100, AvidXchange, Self Storage Manager or comparable property-management software, and Veritec or comparable revenue-management technology is a plus.

• Excellent analytical judgment, written and verbal communication, project management, organization, accuracy, and ability to perform under changing priorities.

• Ability and willingness to work on-site in York, Pennsylvania.

Core Competencies:

Business and financial acumen; Power BI and data-visualization expertise; self-storage and revenue-management knowledge; analytical problem solving; systems thinking; process improvement; data storytelling; customer-service orientation; intellectual curiosity; initiative; accuracy; accountability; adaptability; and cross-functional collaboration.

Physical Requirements:

• Duties are generally performed in a standard indoor office environment.

• Ability to remain stationary and use a computer for prolonged periods; occasional bending, reaching, and repetitive motion may be required.