Predictive Analytics Model Developer

Who we are

Shellpoint Mortgage Servicing (SMS) is one of Americas top-five non-bank mortgage-servicing companies. What is mortgage servicing? Our clients are businesses that own mortgage loans (such as banks and real estate investment firms). On their behalf, we manage (or "service") their loan portfolios, which means that we collect homeowners mortgage payments, pay their tax and insurance bills, and help homeowners in default to get current.

Summary:

We are building our predictive analytics platform so we can help our customers make complex financial decisions and run our business efficiently. The predictive analytics model developer will combine strong data exploration, statistical modeling, communication and collaboration skills to deliver analysis and models that help the business understand borrower probability of default under various circumstances and optimize the opportunity to keep homeowners in their homes.

Responsibilities Include:

• Become the subject matter expert on delinquency and default trends in our portfolio and across the US housing market. Do exploratory data analysis and collateral surveillance to understand emergent trends and factors driving delinquency.

• Work with a seasoned team of servicing and collections experts to create models which help our business identify opportunities and trends in collections and calling campaigns. Create models with an eye towards recalibration and adjustment for exogenous variables such as government housing policy changes.

• Evaluate model tracking error, drill down into model weaknesses, understand model strengths.

• Backtest your models and use subpopulation analysis to gain a deep understanding of model performance.

• Deliver and deploy models into production environments; understand how users are leveraging your models.

• Explain model analytics to business users and work with business to improve model capabilities; document your models for technical and non-technical audiences.

• Do ad hoc data analysis to answer questions which emerge in a fast-moving borrower market

Qualifications/Skills Required:

• 2-5 years of experience using Python, R, SQL, AWS to build econometric models

• Familiarity with U.S. housing market, housing policy and mortgage products.

• Knowledge of mortgage or other retail loan default modeling techniques

• Familiarity with mortgage servicing rights, whole loans, and other consumer loan products

• Familiarity with statistical regression techniques and predictive analytics methods

• Ability to work with software developers, data engineers; understand the software development process and use reproducible research techniques

• Excellent communication skills and ability to collaborate effectively with a team

Educational Requirements:

• Advanced degree in a quantitative discipline such as financial engineering, math, statistics, science, quantitative economics.

Benefits
* Three weeks PTO (paid time off) for vacation and sick days.
* Paid holidays.
* Medical, dental, vision, life, and pet insurance.
* Short- and long-term disability insurance.
* Adoption- and tuition-assistance programs.
* 401k matching program.
* Performance-based annual bonuses.
* Advancement opportunities

Equal Employment Opportunity
We're proud to be an equal opportunity employer- and celebrate our employees' differences, including race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, and Veteran status. Different makes us better.

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