Data Scientist, Hub for AI and Data Science Leadership

The Hub for AI and Data Science (HAIL), within the University of Pittsburgh’s Office of the Provost, serves as an academic convening point for AI and data science efforts to:

•    Unify and strengthen existing AI- and data science-related activities across the university’s academic mission.
•    Convene and connect researchers, practitioners, and academic units to support responsible, innovative applications of AI.
•    Engage with shared governance, especially with the Senate Educational Policies Committee, the Student Admission, Aid and Affairs Committee, and the Student Government Board.
•    Expand upon current RDS work, incorporating its people, resources, and commitments while broadening the scope to reflect the rapidly evolving landscape of AI and data science.

The Hub for AI and Data Science Leadership (HAIL) and the Responsible Data Science, AI, and Complexity for Peace (ReDSCAIP) Lab seeks highly motivated and talented data scientists to support their growing portfolio of projects related to responsible AI and data science. This position, funded for a minimum of 2 years, will play a critical role in ensuring that HAIL and ReDSCAIP can create and share data, metadata, and curriculum, build and compute neural network models to improve the performance of projects, and iteratively improve and deploy interactive applications that increase the reach and impact of both organizations. 
 

Preferred Qualifications:

• Experience working in an academic research environment with social science or social science-focused health science teams.
• Knowledge of specific social science data types and methodologies (e.g., survey data, qualitative data, network data).
• Familiarity with interactive data visualization tools and techniques.

 Education: Graduate degree in a Social Science discipline or a related field with a demonstrated focus on data analysis, management, and curation. A PhD is desired.

Performs research, analysis, and modeling on organizational data and data sets utilizing advanced statistical methods to mine and analyze complex and unstructured data sets. Offers complex analysis and utilizes advanced algorithms and statistical software. Adheres to all protocols.

The ideal candidate will have demonstrable experience in managing unstructured and semi-structured data, a keen understanding of the needs of social science researchers, and excellent communication skills for collaborative work with AI systems. Experience with machine learning pipelines, verifying GenAI output with data science techniques and human annotation, geospatial data and models, and knowledge graphs is preferred.

Key Responsibilities:

• Develop, Implement, and Improve Machine Learning Workflows Across Projects
•  Execute and refine replicable and efficient data creation, processing, and documentation workflows for, with a special focus on unstructured and semi-structured information from social science and related data science and AI research and education projects.
• Contribute to external grant applications.
• Be a responsive liaison to the Center for Research Computing and Data.
• Stay up-to-date on relevant neural network architectures and opportunities
• Tracking and providing expertise on the future of work in the age of AI
• Collaborate and communicate with the relevant teams

• Participate in national and international discussions and initiatives related to AI in Workforce development as well as AI for Peace.

   

Must be able to join in-person meetings around campus as required. Must be able to sit for prolonged periods of time.