Spring EQ is a national home equity lender providing flexible and tailored financing solutions directly to consumers with a national network of experienced brokers and partners. Since its founding in 2016, Spring EQ is among the fastest growing and highest-rated home equity financing partners in the United States. Spring EQ offers a broad range of home equity products and delivers a simple and streamlined process that results in faster funding, trustworthy loans, and less frustration for consumers today. To learn more about Spring EQ, visit www.springeq.com.

At Spring EQ, it is our mission to empower homeowners and buyers to achieve and maximize the value of homeownership in a simple, fast, and ethical manner.  Our values are to

• Be kind and treat all people – teammates, customers, and vendors – with respect and consideration  
• Be adaptable and embrace change
• Be accountable and take responsibility and deliver the effort to fully complete the task
• Be better and strive for continuous improvement in ourselves, our team, and the company for our customers
• Be part of the solution and solve problems, find the answers, and collaborate
• Work hard, have fun, and get things done

We’re seeking a driven and detail-oriented Data Analyst with 3–5 years of experience in data analytics and reporting, preferably within the mortgage industry. The ideal candidate has strong technical skills in SQL and Tableau, a solid understanding of mortgage operations, and the proven ability to drive strategy, influence decisions, and help improve sales and operational performance from their clear and concise analytical findings.

• Develop and maintain dashboards, reports, and visualizations using Tableau and SQL to support business stakeholders and identify performance improvement opportunities.
• Analyze data to identify trends, patterns, and actionable insights.
• Craft clear, compelling narratives from data and present them to both technical and non-technical audiences.
• Audit work to ensure accuracy.
• Partner with business teams to understand objectives and deliver data-driven solutions.
• Perform deep-dive analyses on pull-through, turn time, and other key performance metrics.
• Support forecasting and predictive modeling initiatives (experience in this area is a plus).
• Collaborate with coworkers across sales, operations, and leadership to shape priorities and guide tactical execution.

• Minimum Bachelors degree in Business, preferably finance
• 3–5 years of experience in a Data Analyst or Data Scientist role, ideally within mortgage origination or servicing.
• Proven expertise in SQL and Tableau (Tableau Desktop Certification preferred).
• Strong analytical and problem-solving skills, with great attention to detail and accuracy.
• Strong business acumen with the ability to connect data to business outcomes.
• Excellent communication skills – you can influence through data, not just report it.
• Exposure to forecasting or predictive modeling is a plus.
• Hands-on Python experience a big plus.

Industry Knowledge:

• Familiarity with mortgage origination workflows, including CRM, loan origination, underwriting, and servicing.
• Experience analyzing pull-through rates, application-to-funding turn times, and operational KPIs.
• Understanding of market trends and their implications for mortgage lending strategies.

Technical Skills:

• Proficient in Tableau, Excel, and other BI tools.
• Strong command of SQL for querying and data transformation.

Experience with Python, SAS, or R for advanced data analysis is desirable.

Physical & Mental Abilities Requirements:

Physical Abilities

• Office Environment: Ability to work in an office environment, sitting for extended periods, using a computer, and attending meetings.
• Technology Use: Proficiency in using computers, business intelligence software (e.g., Tableau, Power BI), and other data management tools. Ability to interpret and manipulate large datasets using databases and analytics software.
• Communication: Ability to communicate findings effectively with team members, management, and other stakeholders through presentations, reports, and meetings.
• Document Handling: Ability to manage and review both digital and physical documents, ensuring data accuracy and completeness.

Mental Abilities:

• Analytical Thinking & Problem-Solving:
  • Strong analytical skills to interpret complex data and draw meaningful insights. Ability to identify trends, correlations, and anomalies that inform business decisions.
  • Ability to solve problems by analyzing data patterns and translating them into actionable recommendations.
• Attention to Detail:
  • Exceptional attention to detail when working with large datasets to ensure the accuracy and completeness of the analysis and reporting.
  • Ability to detect errors in data, resolve discrepancies, and ensure data integrity throughout the process.
• Data Modeling & Forecasting:
  • Knowledge of statistical methods and techniques for data modeling, regression analysis, and predictive analytics to forecast future trends.
  • Ability to build and test models that help predict business outcomes such as loan defaults, borrower behavior, and operational efficiency.
• Critical Thinking:
  • Ability to apply critical thinking to interpret complex data and recommend changes that improve business outcomes.
  • Evaluate and prioritize data insights to make informed, effective decisions that align with business goals.
• Communication Skills:
  • Excellent written and verbal communication skills for presenting complex data findings in a clear and concise manner to both technical and non-technical stakeholders.
  • Ability to present data-driven insights in a way that is actionable and easy to understand for business leaders.
• Time Management & Organization:
  • Ability to manage multiple projects and deadlines simultaneously, ensuring timely completion of reports, dashboards, and analysis.
  • Strong organizational skills to maintain and track various datasets, reports, and projects, while adhering to deadlines.
• Collaboration & Teamwork:
  • Ability to collaborate with cross-functional teams, providing data analysis and insights that support business objectives.
  • Work effectively with others to achieve common goals and foster a cooperative team environment.
• Business Acumen:
  • Strong understanding of mortgage industry operations, KPIs, and performance metrics to ensure data analysis aligns with organizational goals.
  • Ability to understand business processes and how data-driven insights can improve performance and strategic initiatives.