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Position Overview:
Are you good at developing practical solutions for hard problems? Are you interested in climate risk research and how climate change impacts mortgage industry? Do you want to expand and refine your quantitative skills? We need someone to research how borrowers respond to disaster and climate change risk, someone to model the impact of natural disasters and climate risks on mortgage default and credit losses. If you are determined, self-motivated and persistent in the pursuit of understanding, then apply today to our Portfolio Analytics Team!
Our Impact:
The team is responsible for providing a spectrum of analytics to support climate risk assessment and policy decisions.
• Natural disaster exposure and impact
• Climate risk research
• Credit risk modeling incorporating climate scenarios
• Data gap analysis and mitigation
Our analyses assist senior management’s business decisions!
Your Impact:
• Perform research to understand climate risk, assess the impacts of natural disasters/climate change on default, prepayment and credit losses. Develop strategies to incorporate climate risk into business decision making.
• Evaluate Freddie Mac’s natural disaster/climate change risk exposure and concentration using various catastrophe/climate models
• Combine economic theory, business understanding and quantitative methods to develop and enhance portfolio performance
• Act as subject matter expert in model development, model usability, and model applications
• Perform hands-on analysis on a large quantity of complicated data from many sources with significant variability to discover business logic and make business proposals to the management team
Qualifications:
• Doctorate degree (or Master’s degree with equivalent work experience) in economics, 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.
• Experience with Catastrophe/climate risk model and scenario analysis is a plus.
Keys to Success in this Role:
• Self-motivated and desire to own a project. Ability to multi-task and work efficiently under tight deadlines.
• Ability to translate business requirements to well-defined analytics problems and translate the analytical results back to business language.
• Excellent analytical thinking and problem-solving skills and capability of researching on challenging tasks and actively looking for solutions.
• Good understanding of quantitative/statistical methods and familiarity with mortgage industry.
• Strong presentation and communication skills.
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.
Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.
This position has an annualized market-based salary range of $118,000 – $178,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.
