Location: Pittsburgh, PA

Are you passionate about helping governments and non-profits be more effective with your AI/ML/Data Science skills? We currently have Senior Research Scientist positions for people with PhDs in AI/ML/Data Science (or related areas), industry experience working on real-world problems, and a passion for social impact. Senior Research Scientists will guide educational and training programs, applied research projects with government agencies and non-profits in education, public health, criminal justice, environment, economic development and international development, and research in areas such as interpretability, bias and fairness, and other machine learning methods focused on problems in social sciences and public policy with a strong emphasis on releasing the work through open source code, shared curriculum, and publications.

Ideal candidates will have 5+ years of industry experience (outside classrooms) building and deploying data-intensive python systems in production, care about the world, and like to work with other people with different backgrounds.

We are a team at Carnegie Mellon University (in Pittsburgh) across the School of Computer Science and the Heinz College of Public Policy focused on using AI, machine learning, and data science to have a positive impact on society. Our interdisciplinary group works at the intersection of research, practice, and education to improve society and public policy.

Much of our group’s work surrounds applied research projects focused on positive and equitable social impact. Senior Research Scientists in the group will participate in work at the intersection of research questions and these applications, such as:

1. Research investigating the measurement and mitigation of bias and disparities in ML-assisted decision making systems in public policy contexts, including empirical studies expanding on our project work as well as the development of new tools
2. Explorations of model interpretability systems to help improve the overall performance of human-ML systems, such as decisions about whether to implement or override specific model recommendations, mapping appropriate interventions to people with need, or debugging and refining models themselves
3. New projects with government and non-profit organizations as they arise, spanning a wide range of policy domains, including social justice, healthcare, education, public safety, economic development, environment, and more

Responsibilities:

• Conducting research focused on bias and fairness in machine learning, model explainability, or methods that are tailored to the nuances of problems in public policy
• Coordinating with government and non-profit partners, including scoping, ongoing updates, field trials & evaluation, and eventual implementation & deployment
• Contributing to open source tools for building, evaluating, and mitigating disparities in machine learning models built for social good applications
• Guiding educational programs, including courses at CMU and/or our summer Data Science for Social Good Fellowship
• Playing a technical role in applied projects, similar to those described above 
• Mentoring students and research associates who work with the group

Qualifications:

• 3+ years of industry/government experience required working on real-world problems 
• Master’s degree required (Ph.D. preferred), preferably in computer science, statistics, or quantitative natural or social sciences
• Strong Python experience
• Experienced in using databases
• Expertise in data analysis and machine learning using python, especially using modules such as statsmodels, scikit-learn, pandas, sqlalchemy, etc.
• Passion for making a social impact and working with governments and non-profits

Carnegie Mellon University offers full-time employees a wide range of benefits, including health, dental, vision, transit, and retirement, as well as parental leave and tuition benefits. You can learn more here.