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At Freddie Mac, our mission of Making Home Possible is what motivates us, and it's at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

Position Overview:

In this role you will advance Enterprise Risk's assessment of Multifamily credit risk through novel use of data and analytics. As part of an analytics team, you will collaborate with colleagues to develop a data-driven approach to independent assessment of the credit risk of Freddie Mac's Multifamily loan acquisitions. This work will leverage advanced analytics to measure past performance of the portfolio, to assess the impact of macroeconomic and other risk drivers, and quantify the risk of new business. You will study Multifamily credit models and evaluate their use in various business applications, and you will provide feedback and effective challenge to improve Multifamily credit risk measurement and risk management across the Enterprise.

Your work supports on-going quantitative assessment of Multifamily credit risk as well as measurement of the risk impact of key policy changes. This position requires skilled work with large data sets and statistical models in the context of multifamily lending. Working knowledge of multifamily lending is needed for this job and continued growth in multifamily domain expertise will be key to success.

In this role, you are expected to scope and manage large projects; to clearly plan and document your work; to implement quality controls; and to present insights through clear written communication.

Our Impact:

The Financial Risk team within the Enterprise Risk Division is responsible for oversight and effective challenge of the company's most important risks, including credit, market, and liquidity risks. Together, we:

• Establish governance, policies, and standards that define how the company manages financial risks to support safety and soundness

• Monitor and report on the risk and control profile, financial risk appetite, and performance of risk indicators and metrics against thresholds and limits

• Communicate enterprise-wide risk management issues and emerging risks and monitor effective and timely issue resolution

• Provide timely and independent oversight and effective challenge of the company's financial risk management practices and risk-taking activities

• Assess risk to earnings and capital across a range of scenarios

• Execute an integrated oversight plan in collaboration with Operational Risk and Compliance to support the Chief Risk Officer in providing senior management and the Board with an enterprise view of risks

Your Impact:

As Lead- Multifamily Credit Risk Analytics, you will:

• Identify trends and emerging risks in Multifamily lending through analysis of both internal and external data and information

• Develop and maintain analytical frameworks to assess Multifamily loan performance and underwriting policies

• Conduct scenario analysis to support assessment of credit policy changes and for the ongoing support of the company's risk appetite

• Evaluate and monitor the company's risk appetite metrics and KRIs

• Enhance the team's risk assessment capability by building subject matter expertise in risk models, statistical methods, machine learning and AI capabilities, credit policy, credit risk, and technical data skills

• Communicate and collaborate across teams both within the Enterprise Risk Division and with first line partners in the Multifamily business. Present analysis to senior leaders and to internal and external stakeholders

Qualifications:

• PhD in economics, finance, statistics, or related quantitative discipline with 3+ years' experience, or Master's with 5+ years relevant experience.

• Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large datasets. Qualifying coursework may include statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods/modeling

• Experience in multifamily lending, with working knowledge of key underwriting concepts

• Expertise in credit risk and credit loss estimation, including working knowledge of common modeling approaches

• Strong decision-making skills with the ability to work under pressure effectively to resolve critical issues

• Experience with analyzing large and complex data sources and conducting analysis using software and tools (e.g., Python, R, SQL, Snowflake). Experience presenting analysis, including preparation of charts and graphs (e.g., Tableau, Excel)

• Excellent verbal and written communication skills with the ability to communicate complex information to a variety of audiences, including senior management and regulators, in a clear and actionable manner

• Demonstrated track record of managing large-scale and complex projects and evidence of success in both independent work and team collaboration

Keys to Success in this Role:

• Excellent quantitative, analytical, problem-solving, and critical thinking skills with an ability to explore and leverage new technical skills when needed

• Excellent communication and presentation skills both verbal and written

• Strong relationship-building skills to facilitate collaboration and improved risk management across the enterprise

• Deep curiosity about multifamily mortgage products and credit risk

• Proven ability to analyze risk using quantitative and qualitative information.

• Ability to work both independently and collaboratively, seeking timely feedback on work and providing support to the team

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

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals 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 time

FLSA Status:Exempt

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 $144,000 - $216,000 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.