Quantitative Analytics Professional (Hybrid Work Schedule)

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Freddie Mac’s Single-Family Division is currently seeking a Quantitative Analytics Professional to be responsible for the development and execution of statistical models and applications in support of business and risk decisions as a member of the House Price Modeling Team. Apply now and learn why there’s #MoreAtFreddieMac!

**This position is a hybrid work schedule, requiring 2 days in the office and 3 days remote** 

Our Impact:

Our team is responsible for the development and analytic support of the House Price Index model, House Price Forecast model, Servicing model, Counterparty Default Model, Affordable Forecast Model, and Benchmarking Default Costing model. Our models are behind many key business initiatives at Freddie Mac such as Credit Risk Transfer, Portfolio Management, Collateral Valuation, Risk Management, and Affordable Housing. We are guided and empowered by several core principles, including the belief that cross-disciplined approaches are far more likely to produce breakthrough models. We recognize that to be at our best we need to build an organization that allows individuals to learn about and participate in a variety of models and modeling techniques.

In our team, candidates work with enthusiastic and collaborative professionals with a diverse set of backgrounds in econometrics, statistics, machine learning and analytics to support and advance Innovative analytics and develop pioneering solutions to convert insights into actions. Applying their quant skills, candidates routinely extract, understand and analyze data in our wide repository of sources, and further produce insights and build models that will inform Freddie Mac’s decisions on our mortgage portfolio. Candidates have the opportunity to perform a wide range of analyses with high impact on management decisions.

Your Impact:

• Developing analytical methods and models that assess the credit risk of new and existing financial and mortgage products.
• Conducting research on enhancements to the existing models, and applying industry best practices and techniques to meet various business needs.
• Providing innovative, thorough and practical solutions to an extensive range of demanding and complicated problems.
• Implementing statistical models in efficient software languages, coding model prototypes for specification and test cases, modifying source codes in the existing application.
• Coordinating the testing through the model implementation, conducting back tests to monitor the model performance, and performing economic tests and stress tests to validate the model forecast results.
• Providing modeling and analytical support to a line of business or product area, functioning as day-to-day technical specialist.
• Preparing documentation for the technical analytics and rationale through the model development to comply with model oversight and support model review for approval.
• Working under limited direction, independently resolving and developing approach to solutions.
• Collaborating with team members, analyzing, documenting, and communicating research results
• Interacting across organization lines to achieve business objectives

Qualifications:

• Master's degree in statistics, data science or a related quantitative field.
• Coursework or work experience applying predictive modeling techniques from data science, statistics, machine learning, and econometrics to large data sets. Qualifying coursework may include--but is not limited to--data science, statistics, machine learning, optimization, numerical analysis, scientific programming, computational methods, supervised learning, unsupervised learning, text mining, and image analysis.
• Coursework or work experience writing computer programs to implement data science pipelines and predictive algorithms. Programming languages may include--but are not limited to--Python, R, SQL, Java, SAS, and MATLAB.
• Coursework or work experience using technologies for manipulating structured and unstructured big data. Big data technologies may include--but are not limited to--Hadoop, Hive, Pig, Spark, relational databases, and NoSQL.

Keys to Success in this Role:

• Strong oral and written communication skills with ability to succinctly describe complex technical scenarios in simple, easily-understood terms
• Solid oral and written communication skills. Ability to pitch and storyboard a project.
• Exceptional quantitative, empirical analysis, and research skills
• Positive and independent thinking
• Strong hands-on ability to handle and process large quantity of structured and unstructured data
• Strong desire and ability to learn new big data and machine learning technologies.

Current Freddie Mac employees please apply through the internal career site.

Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you’ll do important work for the housing finance system and make a difference in the lives of others.

We are an equal opportunity employer and value diversity and inclusion at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by applicable law. We will ensure that individuals with differing abilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.