Job Description

Zeitro is an early-stage startup based in Silicon Valley focused on teaching machines to understand the mortgage and provide related services to all stakeholders in the mortgage industry. We are looking for Mortgage experts to join our fast-growing team, integrate your profound industry knowledge with our technology platform to revolutionize the end-to-end landscape of the mortgage industry.

You will work along with series technology entrepreneurs and talented Machine Learning engineers while building out our next-generation products. You will witness how we use top-notch technology to alter the Mortgage shopping experience from a Labor-intensive practice to a fully automated process.

WE ARE LOOKING FOR SR LOAN PROCESSOR / SUBJECT MATTER EXPERT:

ROLE AND RESPONSIBILITIES:

• Educate members about the loan process. Teach the engineers how processing a loan works.

• Work with Loan Officers to process loans and close deals. Work with Lenders and send loans through, manage conditions, understand loan products, rates, and credit union guidelines that apply to the loan request.

• Responsible for processing all types of residential mortgage applications,

• Review and evaluate loan file documentation including AUS findings, credit reports, preliminary title reports, flood certifications, appraisals and income, and asset documentation prior to forwarding the file to an underwriter.

• Responsible for providing administrative support for all real estate loan closing activities.

• Act as the primary contact for Lenders to follow-up on all underwriter directed and compliance-related conditions.

• Stay informed of trends and developments in the local real estate market, needs of our members as well as changing rules and regulations pertaining to real estate loans. Provide recommendations to management on product and program improvements.

• Proactively make follow-up calls for Member inquiries and incomplete applications received.

QUALIFICATIONS:

• 5+ years recent Mortgage Loan Origination experience.

• Entrepreneurial spirit!

• Understand and comply with all applicable credit union policies and procedures as well as governing laws and regulations and FNMA guidelines.

• Respond promptly to requests and questions from internal staff and members.

• Has strong knowledge of loan products (conventional, jumbo, and government).

• Understands processing, underwriting, and/or closing procedures.

Company Description

Getting a mortgage loan should be no more difficult for a borrower than filing a tax return using TurboTax. The current state of the industry is unsatisfactory. Obtaining a loan is a long, convoluted, and cumbersome process. It is also expensive and inefficient: sometimes it is difficult to qualify, and in many cases, the result is suboptimal - both in terms of the rate of the loan, and its price. The main reason for these inefficiencies is that the process is human-operated. We are teaching a robot to do this job for the whole US market. Two trends are happening. One is the digitization of the back-end communication between the mortgage ecosystem participants in the back end. The other one is the availability and constant improvement of engineering-grade toolsets for AI.It is now feasible to create a service that connects to hundreds of lenders, utilizes modern NLP, and ML technologies, and fully automates the workflow based on implementing the Knowledge Graph database with all the rules, relationships, mortgage products, and understanding of documents. The success of applying the digital transformation, AI, and data science methods to a traditional industry depends on combining the technical chops with in-depth domain knowledge of the existing rules, processes, and peculiarities. Teams focused exclusively on AI methods fail because of the under-appreciation of this domain expertise. Our team includes three competencies: seasoned mortgage professionals with this kind of formal and informal knowledge, Silicon Valley industry veterans, who have built successful cross-discipline products, and companies before, and young data scientists eager to apply their NLP and AI skills to practical problems.