Position Overview:

Are you passionate about data? Are you curious and analytical? Do you thrive on working in a team environment?

Freddie Mac's Multifamily Portfolio and Risk Management team needs creative, forward-thinking individuals like you! We are seeking a Quantitative Analytics Professional who will be responsible for engaging the key Multifamily business partners to ensure the reasonableness and consistency of quantitative models, analytics and methodologies used in risk management and decision making in Multifamily business.

Our Impact:

We are the owners and developers of all major Multifamily credit, market risk and business decision models/tools. Our goal is to develop and apply all quantitative models and advanced data science tools to facilitate Multifamily risk management and optimize portfolio strategies.

Our team is also responsible for Multifamily data analytics, regulatory capital, stress testing and business initiatives. This is an increasingly critical role given our focus on safety and soundness in multifamily business as well as the emerging risk management under the dynamical market environment.

Your Impact:

• Lead efforts on data strategy, analytical tool design, and uses of Multifamily models; provide thoughtful inputs on development of Multifamily data, advanced analytics, and model assumptions/methodology.
• Lead best practices and improvement of Multifamily data management and analytical products to ensure adherence to industry standards and regulatory compliances.
• Collaborate with cross-functional teams to implement data strategy and enhance data uses and data-driven culture.
• Design and implement viable analytical tools/applications, data research and integrated reporting platforms for Multifamily management, business users and risk managers.
• Actively build and engage data science & engineering community through effective communication and leadership.
• Respond quickly with a small team to urgent data analysis requests.
• Build strong productive relationship with various stakeholders across three lines of risk governance.

Qualifications:

• Master's degree in data science, statistics, mathematics, computer 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.
• Demonstrated experience and expertise in quantitative data management, financial model development, credit risk evaluation and model risk management.
• Strong analytical and problem-solving skills with a high level of attention to details.
• Strong interpersonal and communication skills, particularly written communication skills.
• Self-motivated, with the capability of managing multiple priorities and efficient in proposing solutions.

Keys to Success in this Role:

• Data-oriented mindset.
• Intellectual agility and interpersonal flexibility.
• Strong time-management, planning, and communication skills.
• Extensive knowledge and experience in data-driven solutions, analytics, and software development.
• Ability to work with and collaborate across teams and where silos exist.
• Skilled and innovative problem solver.

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

Time-type:Full time

FLSA Status:Non-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 $105,000 - $157,000 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.