Senior Mortgage Credit Modeler

Senior Mortgage Credit Modeler

Experience:

Salary :

Preferred Notice Period

Shift

Opportunity Type:

Placement Type:

(*Note: This is a requirement for one of Uplers' Clients)

Must have skills required :

mortgage credit risk modeling, Python/R/C++

Riskspan (One of Uplers' Clients) is Looking for:

Senior Mortgage Credit Modeler who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.

Role Overview Description

Job Requisition: Senior Mortgage Credit Modeler

Position: Mortgage Credit Modeler

Location: Bengaluru - hybrid

Department: Quantitative Research & Analytics

Role Summary

We are seeking a quantitative modeler with deep expertise in mortgage credit risk to design and implement advanced statistical and econometric models. This role will focus on loan-level performance modeling (delinquency, prepayment, default, loss given default) and structured mortgage asset valuation. The ideal candidate will combine rigorous quantitative training with hands-on experience in coding, model development, and empirical research.

Core Responsibilities

• Develop and enhance loan-level mortgage credit risk models (transition matrices, hazard models, competing risks, survival analysis).
• Implement econometric and machine learning approaches for prepayment, default, and severity modeling.
• Conduct robustness checks of model estimation and sensitivity analysis to assess model robustness.
• Analyze large-scale loan-level datasets (e.g., GSE loan-level, CoreLogic, Intex, private-label RMBS).
• Build and document models in Python/R/C++, ensuring reproducibility and version control.
• Partner with structured finance and risk teams to integrate models into pricing, stress testing, and risk management frameworks.
• Research macroeconomic drivers of mortgage performance and their incorporation into stochastic scenario design.
• Author technical model documentation and research notes for internal stakeholders, model risk management, and regulators.

Technical Qualifications

Required:

• Masters or Ph.D. in Quantitative Finance, Statistics, Econometrics, Applied Mathematics, or related quantitative discipline.
• 7+ years of direct experience in mortgage credit risk modeling or structured finance analytics.
• Advanced skills in statistical modeling: survival analysis, proportional hazard models, logistic regression, generalized linear models, panel data econometrics.
• Strong programming expertise in Python (pandas, NumPy, scikit-learn, statsmodels) or R.
• Proficiency in handling big data (SQL, Spark, Snowflake, and cloud-based data environments).
• Deep knowledge of mortgage credit risk dynamics, housing market fundamentals, and securitization structures.

Preferred:

• Experience with Hierarchical models, and Monte Carlo simulation.
• Knowledge of machine learning algorithms (e.g., gradient boosting, random forests, neural nets) applied to credit modeling.
• Familiarity with stress testing frameworks and regulatory model governance needs.
• Background in RMBS cash flow modeling and structured product analytics.

This role is highly technical and research-driven. Candidates should be comfortable working with complex datasets, formulating empirical hypotheses, and coding full modeling pipelines from data ingestion through validation and deployment.

How to apply for this opportunity:

Easy 3-Step Process:

2. Upload updated Resume & Complete the Screening Form

3. Increase your chances to get shortlisted & meet the client for the Interview!

About Our Client:

RiskSpan uncovers insights and mitigates risk for mortgage loans and structured products. The Edge Platform provides data and predictive models to run forecasts under a range of scenarios and analyze Agency and non-Agency MBS, loans, and MSRs. Leverage our bleeding-edge cloud, machine learning, and AI capabilities to scale faster, optimize model builds, and manage information more efficiently.

Our industry-leading consultants will design and develop custom solutions, automate your workflows, and bring your analytics to life.

Leading capital market, banking and insurance companies choose Edge, consultants, or a perfect mix of the two to make their data beautiful.

About Uplers:

Uplers is the #1 hiring platform for SaaS companies, designed to help you hire top product and engineering talent quickly and efficiently. Our end-to-end AI-powered platform combines artificial intelligence with human expertise to connect you with the best engineering talent from India.

With over 1M deeply vetted professionals, Uplers streamlines the hiring process, reducing lengthy screening times and ensuring you find the perfect fit. Companies like GitLab, Twilio, TripAdvisor, and AirBnB trust Uplers to scale their tech and digital teams effectively and cost-efficiently.

Role & responsibilities

Preferred candidate profile