Senior Data Analyst, Valon Mortgage

Remote Full-time
About the Company Valon ’s mission is to empower every homeowner. We believe the journey of home ownership starts when you get your keys, but lasts far beyond. We’re creating a world where home ownership comes with ease, security, and financial know-how. Our growing team of engineers, operators, product enthusiasts, and experienced servicing professionals are leveraging technology to fundamentally improve the homeownership experience. Through mortgage servicing—the process of paying off one’s mortgage— Valon is taking the first step in transforming the industry one homeowner, and lender, at a time. About the Role: We are hiring a senior data analyst for our Valon Mortgage (VM) analytics function. This team is responsible for providing analytical support across Valon 's operational business including audit/exam fulfillment, SLA monitoring, performance management, investigations, and custom reporting. You will partner with business leaders to improve operational visibility, own externally-facing reports to clients, create internally-facing dashboards, and create scalable solutions to meet Valon ’s data needs.The right candidate is analytical, works well under changing circumstances, and has a good mix of technical skills and business intuition. Responsibilities Build knowledge and expertise around the data tables across all areas of the business. Write SQL queries, build dashboards, and conduct ad hoc analysis to empower operational leaders to understand business performance, make effective decisions, and root cause results. Own and fulfill third-party audit, exam, and regulatory reporting. Manage timelines, perform data QA, and deliver clear, defensible outputs to partners and regulators. Maintain and evolve Valon ’s SLA reporting process. Work with other data analysts and data engineers to make improvements to data models. Ideal Background 8+ years of full-time work experience in data analytics or business intelligence, ideally at a mortgage servicer or financial institution. Expertise in SQL required (Python skills a plus). Expertise in Google sheets and/or Microsoft Excel. Experience using data visualization tools (Hex, Looker, or equivalent). Fast learner with problem solver mentality. Ability to solve problems independently and build processes around situations that have not been encountered before. Experience working with cross functional data team members. Minimum Qualifications Bachelor’s Degree in Computer Science, Data Analytics, or a similar field Benefits Compensation: competitive salary and 401k plan Health well-being: we’ll invest in your physical and mental well-being with comprehensive medical, dental, vision benefits Grow together: Company wide orientation for you to successfully onboard and other learning development opportunities including regular review cycles that feature 360 degree feedback Generous time off: 17 days paid time off, sick days, and 11 company holidays Baby bonding time!: 12 weeks off for both birthing and non-birthing parents - fully paid so you can focus your energy on your newest addition This Base Compensation pay range applies to our New York City located staff and may differ according to location. New York Base Compensation Pay Range $136,000$180,000 USD Throughout the interview process, please remember that emails will only be from valon.com emails. We won't ever be asking for any personally identifiable information during the interview process itself. Please reach out to [email protected] if you have any requests to verify the authenticity of an outreach. Valon is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. Valon makes hiring decisions based solely on qualifications, merit, and business needs at the time. Originally posted on Himalayas
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