Description

We are building a new team at Carnegie Mellon University across the Machine Learning Department and the Heinz College of Information Systems and Public Policy focused on using Artificial Intelligence, Machine Learning, and Data Science (and other buzzwords) to have a positive impact on society.

Are you passionate about social impact and using your AI/ML/Data Science skills to help governments and non-profits be more effective and equitable in improving society?

Our interdisciplinary group works at the intersection of research, practice, and education to improve society and public policy in close collaboration with local, national, and international governments and non-profits.

Our research is aimed at ensuring that AI and ML systems for social good and policy problems achieve the outcomes they were intended for, with a focus on interpretablity/explainability and bias/fairness/equity. We motivate and apply our research to projects in public health, criminal justice, education, workforce development, economic development, and other areas in close collaboration with governments and NGOs.

Skills and responsibilities

We are building a new team at Carnegie Mellon University across the School of Computer Science and the Heinz College of Information Systems and 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.
 
Your core responsibilities will include:
  • Lead the development of open source software to enable the research and deployment of Machine Learning and AI for social good projects in collaboration with governments and nonprofits;.
  • Work with an interdisciplinary team of computer scientists, statisticians and social scientists focused on data science projects with social impact;
  • Provide expertise and guidance to the rest of the team in building good software and develop tools and methodologies to make that easier;
  • Lead the development of data and computational infrastructure for teaching and doing research on machine learning and AI with data from multiple government agencies and nonprofits.

Details

  • Location:
    Pittsburgh
    ,
    PA
  • Deadline: n/a

Qualifications

Minimum qualifications

  • Bachelor's degree required, preferably in computer science, information sciences, or another relevant field. Advanced degree preferred;
  • 3+ years of previous software engineering work experience (5+ years preferred);
  • Strong Python experience including building, testing, deploying, and maintaining software;
  • Experience in using large, scalable relational databases, ranging from postgresql to redshift. Experience with spatial data (with postgis for example) is a plus. Experience with redis or mongodb is helpful but not required;
  • Expertise in data analysis and machine learning using python is a plus, especially using modules such as statsmodels, scikit-learn, pandas, sqlalchemy;
  • Experience working on real-world problems and passion for making a social impact;
  • Experience building systems with end-to-end data science workflows from ETL to analysis/modeling to prototyping to deployment; 
  • Experience building scalable data pipelines using workflow tools  such as luigi and airflow; Experience developing code in a team environment using git;
  • Experience with managing and developing for/on cloud platforms such as Amazon Web Services (EC2, RDS, RedShift, S3, OpsWorks);
  • Experience with some front-end development and javascript frameworks a plus.