Data Science Advisor

Fannie Mae•Reston, DC

8d•$155,000 - $209,000•Hybrid

About The Position

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home. As a valued contributor to our team, you will act as a coach, mentor, and subject matter expert to drive the success of portions of products or initiatives through the production of insights, new product or change recommendations, process improvement or automation, and predictive modeling. You will apply extensive knowledge of data mining and data analysis methods, be adept with common large data processing techniques, computational programing capabilities, practical problem-solving skills, and have an expert ability to articulate solutions to non-technical consumers or partners. As an advisor, you will partner with data engineering and data management teams, and apply data mining techniques to external or created data sources in preparation for analysis or use of enterprise data assets. You will lead multifamily risk analysis by developing innovative data-driven methods, GenAI Applications and Machine Learning/Predictive models to uncover and assess insights. You will engage in verbal and written communications with senior management, which will require top level engagement skills to synthesize complex ideas and discuss in manner that influences business and strategic actions. You will be required to mentor younger analysts, work across teams, manage multiple projects, and leverage new technologies to enhance analytical approaches.

Requirements

6 years of relevant experience in data science, predictive analytics, optimization , product management functions.
2 + years of hands-on experience in generative AI, machine learning, knowledge graphs and RAG systems and workflow automation .
5+ years of leadership experience building, coaching, and leading high-performing, supporting complex, multi-stakeholder programs in a regulated or governance-driven environment
Proven track record of conducting independent economic and risk analysis or research.
Delivering actionable insights that drive business and strategic decisions with measurable outcomes.
Strong understanding of risk management, multifamily credit risk, real estate and mortgage finance, fixed income and structured products, statistics and optimization techniques.
Management-level communication and influencing skills, with the ability to advise executives and senior stakeholders, challenge assumptions, and explain technical ideas clearly to non-technical audiences.
PHD or Masters in Data Science , Economics, Math, Statistics, or a related field
Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Nice To Haves

PhD preferred in Data Science, Economics, Math, Statistics, or a related field ( or comparable years of experience)
Experience in financial services, mortgage finance, banking, or risk management.
Experience with data analysis, statistics and modelling, Bayesian statistics, optimization, graph theory, options and derivatives pricing.
Experience with CECL Loss Allowance, Basel Capital Rules, Stress Testing and CRE Valuations
Experience working with and innovating with Gen-I. leading AI-enabled transformation in analytics, risk management, financial services, or another highly regulated enterprise environment.
Experience with GenAI/LLMs, retrieval-augmented generation, NLP, anomaly detection, machine learning, reinforcement learning, orchestrated multi-agentic workflows, or knowledge graphs.

Responsibilities

Collaborate with product and/or business owners, data engineers, and platform teams to understand business needs and current capabilities, data availability, and alternative uses.
Develop and advise on the implementation of new statistical modeling capabilities to solve technical business problems and inform the team's technical direction.
Apply and develop advanced analytic capabilities to enhance the delivery of business applications, and support the integration of data and statistical models or algorithms.
Apply extensive knowledge of practices in research and testing for product development, deployment, and maintenance.
Design new modeling applications to support risk measurement, financial valuation, decision making, and business performance for parts of products or initiatives.
Design data visualizations, technical documentation, and non-technical presentation materials to communicate new ideas and high-impact solutions to business partners
Apply understanding of relevant business context to interpret model results, monitor performance, and assess risks.
Communicate complex technical subject matter clearly and concisely, both verbally and through written communication, such as white papers, review reports, or workpapers