Quantitative Analytics Senior
Headquarters 4, United States
Full Time Senior-level / Expert USD 125K - 187K
Freddie Mac
We are supporting America's homeowners and renters while serving as a stabilizing force in the U.S. housing finance system.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:Servicing Portfolio Analytics team in Freddie Mac Single Family division is seeking a Servicing Portfolio Analytics Senior to design, develop, and implement the methods and tools of assessing Freddie Mac portfolio servicing performance. The team is looking for a highly motivated analyst passionate about data and applying quantitative methods to assess the performance of mortgage such as evaluating credit loss, delinquency and default risk, and the impact of policy. Apply now and learn why there’s #MoreAtFreddieMac!
Our Impact:The team is responsible for providing analytics to support overall servicing portfolio management.
Assist senior management to make decision on portfolio management strategies with our data-based insight on the performance of servicing portfolio.
Our analytics results are broadly shared by the company.
Combine economic theory, business understanding and quantitative methods to develop and enhance mortgage performance evaluation processes, measurement metrics and analytical tools to support business decisions.
Develop analytics to value the risk, benefits and cashflow associated with portfolio performance and policy.
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
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.
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.
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.
A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.
CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.
Time-type:Full timeFLSA Status:ExemptFreddie 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 $125,000 - $187,000 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.Tags: Bayesian Finance Java Machine Learning Mathematics Matlab Monte Carlo Predictive modeling Privacy Python R SAS Security SQL Statistics
Perks/benefits: Career development Competitive pay Equity / stock options
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.