Quantitative Analytics Director

Freddie Mac•McLean, VA

2d•Onsite

About The Position

The Quantitative Analytics Director is a strategic analytics leader responsible for transforming complex data into actionable business insights for senior executives and key stakeholders. This role emphasizes insight generation, decision support, and business impact while requiring strong fluency in quantitative methods, large-scale data analysis, and advanced analytical techniques. The Director will lead the development and implementation of analytical workflows that accelerate insight creation, improve analytical efficiency, and enhance decision-making. A critical responsibility of the role is ensuring these AI capabilities are developed, governed, and deployed in a controlled, transparent, and compliant manner. This position leads a team of analysts and data scientists and serves as a key partner across business, risk, technology, and analytics functions. Our team plays a critical role in helping Freddie Mac understand, anticipate, and manage credit risk across a dynamic mortgage market. By bringing together deep insights on how credit risk intersects with other aspects of our business, we provide timely insights that inform business decisions, strengthens governance, and supports the company’s mission. This is a role with opportunities to shape frameworks, influence cross-divisional outcomes, and engage with senior leaders on issues that matter to Credit Risk Management (CRM) as Freddie Mac balances credit risk and other scorecard items.

Requirements

Advanced degree in a quantitative field such as Statistics, Mathematics, Economics, Data Science, Operations Research, Engineering, or a related discipline.
At least 12 years of experience in quantitative analysis, data science, risk analytics, or a related field.
At least 4 years demonstrated experience leading and developing analytical teams.
Strong expertise in quantitative methods, statistical analysis and working with large datasets.
Experience developing, AI-enabled analytical solutions.
Strong executive communication and presentation skills, including the ability to translate technical concepts into business implications.
Proven ability to influence senior stakeholders and drive strategic decisions through analytics.

Nice To Haves

Experience with internal models, metrics and frameworks central to measuring risk and returns of SF business at Freddie Mac.
Experience with modern analytics, data engineering, and AI platforms.
Ability to convert complex analytical findings into clear business actions.
Strong judgment in balancing innovation with governance and control requirements.
Collaborative leadership style with a focus on developing talent and building partnerships with peers and stakeholders.
Passion for leveraging data and AI to create measurable business value.

Responsibilities

Lead diverse Quantitative Analytics for Credit Risk Management (CRM).
Translate complex business questions into data-driven analyses and executive-level insights.
Develop clear, compelling narratives that inform strategic decisions by senior leadership.
Identify emerging trends, risks, opportunities, and business drivers through advanced analytical techniques.
Synthesize information from multiple data sources, models, and analytical frameworks into actionable recommendations.
Apply advanced quantitative methods to analyze large and complex datasets.
Leverage internal analytical and predictive models to generate business insights and recommendations.
Partner with model owners, validation teams, and subject matter experts to ensure appropriate interpretation and application of model outputs.
Maintain strong working knowledge of key enterprise models, methodologies, assumptions, and limitations.
Lead, coach, and develop a high-performing team of analysts and data scientists.
Prioritize work, allocate resources, and ensure delivery of high-quality analytical outputs.
Foster a culture of innovation, collaboration, continuous learning, and accountability.
Support career development and technical growth of team members.
Partner closely with business leaders, risk management, technology, data, and analytics teams.
Influence stakeholders through data-driven recommendations and clear communication.
Drive alignment across teams to ensure analytical insights support strategic business objectives.
Design and implement AI-driven workflows that accelerate the generation of insights and analytical products.
Establish governance, controls, monitoring, and documentation standards for AI-enabled processes.
Evaluate and integrate emerging AI capabilities while ensuring appropriate risk management, transparency, and compliance.
Promote responsible and controlled adoption of AI across the analytics function.