Quantitative Analytics Senior

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

At Freddie Mac, you will do important work to build a better housing finance system and you’ll be part of a team helping to make homeownership and rental housing more accessible and affordable across the nation.

Position Overview:

Are you curious and analytical? Do you thrive on working in a team environment? Are you looking for an inclusive company culture? Freddie Mac’s Single-Family Portfolio Strategy (PS) group needs creative, forward-thinking individuals like you! We want to hire individuals who seek out complex business problems and develop viable solutions. The Quantitative Analytics Senior position is responsible for ensuring the reasonableness and consistency of statistical models, analytics and methodologies used in decision making in the SF guarantee business. Apply now and learn why there’s #MoreAtFreddieMac!

**This position can be performed currently from a remote location in the U.S. but will require presence in a Freddie Mac office in the future.***

Our Impact:

Our team is responsible for forecasting regulatory capital for SF business. This is an increasingly critical role given our regulators’ road map to exit conservatorship and recent FHFA changes to capital standard.

We are also significant users to a number of vert high and high risk SF models. Our goal is to utilize all available models and tools to facilitate and optimize portfolio strategies.

Your Impact:

• Supporting team in managing Loan Analytics Modeling Application (LAMA) with understanding, oversight and documenting default cost calculation
• Accurately review and ensure concise, complete, and transparent model tracking report to SF portfolio division
• Able to execute LAMA, and CCF forecast model and provide insights on results
• Develop resolutions to problems of limited scope following specific and detailed procedures

Qualifications:

• Doctorate degree (or Master's degree with equivalent work experience) in quantitative finance, statistics or a related quantitative field.
• Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large data sets. Qualifying coursework may include—but is not limited to—statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods/modeling.
• Coursework or work experience writing statistical and/or optimization programs to develop models and algorithms. Programming languages may include—but are not limited to—Python, R, SQL, Java, SAS, and MATLAB.

Keys to Success in this Role:

• Intellectual agility and interpersonal flexibility
• Ability to work with and collaborate across the team and where silos exist
• Deep curiosity to learn about new trends
• Ability to utilize data to help inform strategy and direction
• Solid aptitude for solving problems, innovative and out of box problem solver
• Ability to translate complex statistical models and methodologies into simple business terms
• Strong leadership, planning and communication skills