Job Description
About the National Fair Housing Alliance The National Fair Housing Alliance (NFHA) has an opening for a dynamic, results-oriented visionary to serve as Math Science Intern. NFHA leads the fair housing movement and is the nation's only national civil rights organization exclusively dedicated to eliminating all forms of housing discrimination and ensuring equitable housing opportunities for all people and communities. We have a diverse, experienced, mission-driven, and impactful team that has developed equity-based policies at the federal, state, and local levels to expand fair housing opportunities; brought precedent-setting litigation to eliminate some of the most heinous forms of housing discrimination; conducted groundbreaking research to promote equitable solutions; and invested millions of dollars in underserved communities. We have solid relationships, built on trust, with national, regional, and local organizations, and we effectively draw upon these connections to reach vital goals.
We are game changers that millions of people rely upon to advance fair housing in the communities where they live. Where you live matters. It affects every aspect of your life and determines whether you have access to resources—like broadband service, healthcare facilities, fresh land, air, and water, and well-resourced schools—we all need to thrive. Despite important existing federal laws, more than 4 million acts of housing discrimination occur in the U.S. each year, and housing inequality remains stubbornly entrenched. That is why—through its education and outreach, member services, public policy, and advocacy, housing and community development, responsible AI, enforcement, and consulting and compliance programs—NFHA is dismantling longstanding barriers to equity, rooting out bias, and building diverse, inclusive, well-resourced communities. To learn more about NFHA, please visit .
Position Summary The Responsible AI Lab at NFHA envisions a housing system where security, safety, and trust are the cornerstones of every AI-driven decision. Our vision is to ensure that AI systems and tomorrow’s innovations in housing promote inclusivity and equity, avoiding discrimination and segregation. Our mission is to enable fair housing through Responsible AI and future technologies by addressing risks, promoting equity, and advancing innovative technologies. We are committed to ensuring that AI systems and emerging technologies in housing adhere to the principles of security, safety, and trustworthiness, preventing discriminatory outcomes and mitigating segregation patterns.
We are looking for a Math Science Intern to join the Development unit of our innovative, startup-like RAIL team to help advance our mission. The Intern will contribute to the development and deployment of software solutions that advance the Responsible AI team's mission at NFHA. This role focuses on designing, building, and maintaining frameworks, methodologies and techniques that address the ethical, legal, and societal challenges of AI in housing. The Math Science Intern will work closely with cross-functional teams to implement innovative, secure, and reliable theoretical work into research that promotes equity, ensures compliance with civil and human rights laws, and supports the responsible deployment of AI technologies in the housing sector.
We are looking for someone who embraces curiosity and thrives in a dynamic, iterative development environment. We also value team members who question assumptions and excel in adaptive, fast-paced workflows. Visit RAIL microsite to learn more about the team and the core principles that direct the team’s work.
Essential Job Functions Responsibilities Overview - Read theoretical research papers on AI and present the papers to the team .
- Work with RAIL researchers and engineers to select optimal model and preprocessing workflows to align with experimental needs.
- Contribute to research methodology development and help align project needs with technical feasibility
- Assist in manuscript preparation in submission to journals or conferences.
- Stay updated with the latest advancements in ML and AI to ensure the integration of state-of-the-art techniques.
Collaboration - Work closely with AI researchers, engineers, and other stakeholders in the organization to align theoretical frameworks with project goals.
- Participate in agile ceremonies such as sprint planning, stand-ups, and retrospectives to ensure smooth team workflows.
- Contribute to cross-functional projects.
- Share insights and lessons learned with the team to foster a culture of continuous improvement.
Communication - Document technical workflows, processes, and code to ensure knowledge sharing and project continuity.
- Present updates and results to both technical and non-technical stakeholders.
- Provide clear and concise explanations of complex technical concepts when discussing research.
- Actively participate in team discussions, providing constructive feedback and sharing ideas.
Qualifications and Competencies Education & Experience: - Currently pursuing a degree in Mathematics, Computer Science, Statistics, Physics, Pure Chemistry, or a related field.
- Coursework: At least four of the following coursework must be completed prior to applying for the internship.
- Machine Learning Fundamentals – Covers supervised and unsupervised learning, classification, regression, and clustering algorithms, forming the foundation for advanced topics in AI.
- Deep Learning – Focuses on neural networks, backpropagation, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and frameworks like TensorFlow or PyTorch.
- Reinforcement Learning – Explores Markov decision processes, dynamic programming, Q-learning, policy gradients, and applications in robotics, game AI, and real-world control systems.
- Probability and Statistics for Machine Learning – Provides essential knowledge on probability distributions, Bayesian inference, hypothesis testing, and statistical modeling for developing robust machine learning models.
- Optimization Techniques – Teaches gradient-based and gradient-free optimization methods such as stochastic gradient descent, convex optimization, and their applications in training machine learning models efficiently.
Skills: - Strong understanding of ML and AI concepts, including algorithms, statistical methods, and theoretical foundations.
- Adaptability to work with and stay aware of evolving technologies and frameworks.
- Strong organizational and time-management skills to balance multiple projects and deadlines.
- Ability to communicate complex technical information to semi-technical or non-technical audiences.
Expected Hours and Compensation - Minimum 20 hours a week, ideally 30-32 hours a week
- The internship is for 256 hours with a total compensation of $6,400
- The internship is expected to run for 8-10 weeks.
Application Process: Interested applicants should submit a resume, two sample writeups, and a cover letter outlining your relevant experience and why you are interested in the position. Applications without any of the required materials will not be considered. No telephone calls, please.
This position will remain open until filled.
Affirmative Action/Equal Opportunity Statement NFHA values and encourages diversity in its workforce. NFHA supports affirmative action and is dedicated to promoting equal employment opportunities. NFHA does not discriminate on the basis of race, color, religion, national origin, ancestry, citizenship, sex, age, marital status, personal appearance, sexual orientation, family responsibilities, disability, matriculation, political affiliation, or any other category or characteristic protected by the laws of the United States or the District of Columbia.
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