Senior Data Analyst

Senior Data Analyst

Location: Chicago, IL

Work Schedule: 100% onsite (5 days per week) with up to 50 remote workdays annually

We are seeking a Senior Data Analyst to serve as a strategic partner to business and executive leadership, transforming complex mortgage, financial, and operational data into actionable insights. This role is responsible for developing analytical solutions, monitoring portfolio performance, identifying emerging risks and opportunities, and delivering data-driven recommendations that support key business decisions. The ideal candidate combines strong technical analytics skills with business acumen and the ability to communicate insights to senior stakeholders.

Key Responsibilities:

Mortgage Portfolio Analytics & Business Insights

• Perform advanced analysis of mortgage, financial, and operational data to monitor portfolio performance, production trends, loan quality, operational effectiveness, and risk exposure.
• Identify emerging trends, business opportunities, and portfolio risks through data-driven analysis.
• Develop portfolio monitoring frameworks and performance measurement methodologies.
• Conduct ad hoc analyses and provide strategic recommendations to support organizational objectives and executive decision-making.

Reporting & Data Visualization

• Design and maintain executive dashboards, scorecards, and reporting solutions using modern business intelligence tools.
• Create clear and compelling visualizations that communicate complex analytical findings to technical and non-technical audiences.
• Present insights, trends, and recommendations to senior leadership and key stakeholders.
• Deliver reporting that provides visibility into operational metrics, portfolio performance, customer activity, and risk indicators.

Data Management, Automation & Advanced Analytics

• Develop automated reporting, analytical workflows, and scalable data solutions to improve efficiency and accuracy.
• Extract, transform, validate, and analyze data from multiple internal and external sources.
• Establish data quality standards, governance controls, and validation processes to ensure data integrity.
• Identify opportunities to leverage advanced analytics, artificial intelligence, machine learning, and automation to enhance business processes and decision-making.

Cross-Functional Collaboration

• Partner with teams across Risk, Finance, Operations, Business Intelligence, Customer Success, and Data Management.
• Support a data-driven culture by sharing analytical best practices and mentoring junior team members when appropriate.
• Stay informed on mortgage industry trends, housing finance developments, regulatory changes, and emerging analytical technologies.

Required Qualifications:

• Bachelors degree in Data Science, Business Analytics, Economics, Finance, Statistics, Mathematics, Computer Science, or a related quantitative field.
• 4+ years of experience in data analytics, business intelligence, financial analysis, or a related analytical role.
• Advanced SQL experience, including querying, transforming, validating, and analyzing large datasets.
• Experience building dashboards and visualizations using Tableau, Power BI, or similar BI platforms.
• Strong analytical, quantitative, and problem-solving skills with exceptional attention to detail.
• Experience translating complex datasets into actionable business insights and recommendations.
• Strong business acumen and ability to align analytical findings with organizational objectives.
• Advanced proficiency in Microsoft Excel, PowerPoint, and Word.
• Excellent communication and presentation skills, including experience presenting findings to senior leadership.
• Proven ability to manage multiple priorities in a fast-paced environment and collaborate with cross-functional stakeholders.

Preferred Qualifications:

• Experience analyzing mortgage portfolios, mortgage-backed securities, consumer lending portfolios, housing finance programs, or other credit-related financial products.
• Experience with Python, R, SAS, or similar analytical/statistical programming languages.
• Exposure to advanced analytics, machine learning, artificial intelligence, or process automation initiatives.
• Experience supporting financial services, lending, banking, mortgage, or housing finance organizations.