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Mortgage Data Analyst Jobs (NOW HIRING)

Ellisor Group

Mortgage Data Analyst

San Francisco, CA · On-site

Mortgage/Data Analyst Compensation: 100K-135K base No 3rd party/C2C- No sponsorship at this time Client is re-writing the risk model for the non-QM mortgage market -combining data analytics ...

AD Mortgage

Mortgage Servicing Data Analyst

Troy, MI

About this opportunity The Mortgage Servicing Data Analyst is responsible for analyzing mortgage servicing data, identifying trends, supporting operational reporting, improving portfolio performance ...

Prophecy Technologies

Data Analyst

San Antonio, TX · On-site

Analyze data related to mortgage loan servicing, MBS, equities, fixed income, and asset management. * Collaborate with business and technology teams to support data-driven decision-making. Required ...

Purple Drive Technologies

Data Analyst

San Antonio, TX · On-site

TCS Location: San Antonio, TX Data analyst 8+ years of experience in the domain of Banking and ... Mortgage loan servicing, Mortgage-Backed Securities (MBS), Stocks, Options, Commercial lending ...

AmeriSave Mortgage Corp.

AmeriSave Mortgage is a leading online mortgage lender dedicated to simplifying the mortgage ... Position Overview The Capital Markets Data Analyst is dedicated exclusively to supporting the ...

USM

Data Analyst

Mclean, VA · On-site

The position will support Servicing Portfolio Analytics This will require a lot of data validation ... Experience in Data Analytix Prior mortgage industry exp is helpful. Additional Information All your ...

twoharbors

Data Analyst - Loan Boarding

Coppell, TX · On-site

At least 2-4 years of related mortgage servicing experience * Keen analytic skills with a strong ... data analysis. * The noise level in the work environment is usually quiet to moderate, and no ...

Guild

Sr Data Analyst

$109K - $156K/yr

Position Summary Guild Mortgage is seeking a Senior Data Analyst with a strong track record of ... creative thinking and driving transformation in technology-enabled environments and maximizing ...

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Mortgage Data Analyst information

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$34K

$82.6K

$136K

How much do mortgage data analyst jobs pay per year?

As of Jun 13, 2026, the average yearly pay for mortgage data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Mortgage Data Analysts, and how can they be addressed?

Mortgage Data Analysts often encounter challenges such as managing large volumes of complex data from multiple sources, ensuring data accuracy, and keeping up with regulatory changes in the mortgage industry. Addressing these challenges requires strong attention to detail, proficiency with data analysis tools (like SQL, Excel, and Python), and continuous learning to stay updated on industry regulations. Collaboration with IT, compliance, and loan processing teams is essential to verify data integrity and implement process improvements, making strong communication skills equally important.

What are the key skills and qualifications needed to thrive as a Mortgage Data Analyst, and why are they important?

To thrive as a Mortgage Data Analyst, you need a strong background in data analysis, financial modeling, and an understanding of mortgage lending practices, often supported by a degree in finance, statistics, or a related field. Familiarity with data analytics tools like SQL, Python, Excel, and mortgage software systems is typically required, along with certifications such as Certified Mortgage Banker (CMB) being advantageous. Analytical thinking, attention to detail, and effective communication are essential soft skills for interpreting complex data and presenting insights to stakeholders. These skills ensure accurate risk assessments, regulatory compliance, and data-driven decision-making in the mortgage industry.

What does a Mortgage Data Analyst do?

A Mortgage Data Analyst is responsible for collecting, analyzing, and interpreting data related to mortgage loans and lending practices. They use statistical tools and software to identify trends, assess risk, and generate reports that help lenders make informed decisions. Their work helps optimize loan processes, ensure compliance with regulations, and improve customer experience. Mortgage Data Analysts often collaborate with underwriting, risk management, and IT teams to support a company's strategic goals.

Is 40 too late for data science?

For a Mortgage Data Analyst or similar data science roles, starting a career at 40 is feasible as the field values skills, experience, and continuous learning. Many professionals transition into data roles later in life by acquiring relevant certifications, such as in SQL or Python, and building a strong portfolio. Age is less important than your ability to adapt and develop the necessary technical and analytical skills.

What is the difference between Mortgage Data Analyst vs Mortgage Underwriter?

AspectMortgage Data AnalystMortgage Underwriter
Required CredentialsTypically a bachelor's degree in finance, economics, or related field; certifications like CAMS or CFA are a plusUsually a bachelor's degree in finance, economics, or related; certifications like MLO or FHA approval may be required
Work EnvironmentData analysis teams, financial institutions, or mortgage companiesLoan processing departments, banks, or mortgage lenders
Employer & Industry UsageUsed across mortgage lenders, banks, and financial services for data insightsPrimarily in mortgage lending, assessing loan risk and compliance

The Mortgage Data Analyst focuses on analyzing mortgage data to identify trends and support decision-making, while the Mortgage Underwriter evaluates individual loan applications to determine approval risk. Both roles require financial knowledge and work within mortgage institutions, but their core responsibilities differ significantly.

Is a data analyst a high paying job?

A mortgage data analyst is typically considered a well-paying role within the finance and real estate industries, with salaries often above average for entry-level positions. Compensation depends on experience, location, and skills such as proficiency in SQL, Excel, and data visualization tools. Advanced certifications and specialized knowledge can also lead to higher earnings.

What is the salary of data analyst in JP Morgan?

A Mortgage Data Analyst at JP Morgan typically earns between $60,000 and $90,000 annually, depending on experience, location, and specific responsibilities. Entry-level positions may start lower, while experienced analysts with specialized skills can earn higher salaries. Compensation often includes benefits such as bonuses and health insurance.

What does a mortgage analyst do?

A mortgage data analyst reviews and interprets mortgage loan data to assess risk, identify trends, and support lending decisions. They often use data analysis tools and financial models to ensure accuracy and compliance with regulations, contributing to the efficiency of the mortgage process.
More about Mortgage Data Analyst jobs
What states have the most Mortgage Data Analyst jobs? States with the most job openings for Mortgage Data Analyst jobs include:
What job categories do people searching Mortgage Data Analyst jobs look for? The top searched job categories for Mortgage Data Analyst jobs are:
Mortgage Data Analyst jobs near you
Infographic showing various Mortgage Data Analyst job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Part Time. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Mortgage Data Analyst

Ellisor Group

San Francisco, CA • On-site

Full-time

Posted 9 days ago

Job description

Title: Mortgage/Data Analyst

Compensation: 100K-135K base

No 3rd party/C2C- No sponsorship at this time

Client is re-writing the risk model for the non-QM mortgage market -combining data analytics, proprietary risk intelligence, and Loan Defect Insurance to turn mortgage manufacturing risk into quantifiable, insurable outcomes for lenders, investors, and RMBS issuers. Client AI (SAI) is the analytical engine powering this platform, built on neural network triage, hazard-based pricing, and AI-driven defect detection. The Mortgage / Data Analyst is the person who makes SAI's outputs defensible to the outside world -bridging model outputs and real-world loan performance through surveillance reporting, model validation, and institutional counterparty deliverables.

In this role you will:

· Produce surveillance reporting -pool health summaries, delinquency trends, roll rate analysis, and defect emergence narratives supporting institutional counterparty relationships

· Maintain mark-to-market LTV calculations using live HPI feeds and produce early-warning indicators for pools approaching concentration thresholds or deteriorating collateral values

· Own quarterly reinsurer reporting -claims bordereau data, aggregate exposure summaries, and pool performance vs. pricing assumption variance

· Build and maintain investor report templates translating model outputs into plain-language risk narratives for capital markets counterparties

· Perform loan-level file review and model output validation -comparing defect flags and risk scores against loan documents to identify systematic errors or coverage gaps

· Contribute realized loss experience and recovery timing data that calibrates SAI's claims analytics models

The Ideal Candidate:

· Has sat in a loan file and knows what makes a defect real vs. a model flag

· Can translate complex model output into language a reinsurer's credit committee will act on

· Brings equal comfort to Excel and SQL

Basic Qualifications:

· 4+ years in non-QM loan review, mortgage credit risk, or structured finance analytics

· Deep familiarity with non-QM loan types: DSCR, bank statement, asset depletion, foreign national

· SQL and Excel or Python for analysis and reporting

· Performance reports and risk narratives produced for institutional audiences

Preferred Qualifications:

· Quantitative model outputs translated into investor or counterparty-facing narratives

· RMBS or whole loan pool-level surveillance reporting

· Mark-to-market LTV monitoring using CoreLogic, FHFA, or equivalent HPI data

Tech: SQL · Python or R · Excel · Tableau or Power BI · HPI data feeds (CoreLogic / FHFA)