Senior Research Data Scientist

Description

The NYU McSilver Institute for Poverty Policy and Research is committed to creating new knowledge about the root causes of poverty, developing evidence-based interventions to address its consequences, and rapidly translating research findings into action through policy and best practices. 

We are seeking to recruit a Senior Research Data Scientist for the Institute and with a special focus on developing applications and solutions to support our Artificial Intelligence (AI) Hub. The AI Hub at McSilver has been established to investigate how artificial intelligence-driven systems can be used to equitably address poverty and challenges relating to race and public health, and to provide thought leadership on the implications. The AI Hub will address a dearth of information about how AI can impact the lives of people in marginalized communities. Among the hub’s initial areas of focus will be building on the institute’s work to answer whether AI can be used to better predict suicide rates and behaviors by race, geography, income and other demographic variables, with other innovative public health research and interventions to follow. 

POSITION SUMMARY:

Reporting to the Assistant Director for Research and working in collaboration with the Director for Behavioral Health Research and the Executive Director, the Senior Research Data Scientist will provide expertise, leadership, and strategic planning to drive the growth and expansion of research and evaluation projects within the AI data analytics team. This role involves collaborating with faculty and students on cutting-edge research projects and taking responsibility for pursuing, developing, and expanding research-oriented activities with strategic partners and funders. The successful candidate will be instrumental in leveraging AI to address critical public health and social issues, particularly those affecting marginalized communities.

PRIMARY RESPONSIBILITIES:

• Public Health Research and Data Science:

• Perform rigorous data science analyses to provide insights and advancements in public health research and policy, focusing on factors such as suicide risk by race, ethnicity, and other demographic variables.

• Access, validate, and analyze information from multiple data sources by developing, validating, and linking various data sets, including high-risk, health, behavioral, and public data sets.

• Aggregate and analyze population health data, research data, survey data, and other sources to prepare for AI/ML analysis and algorithmic development.

• Build and automate data collection, ingestion, and processing tools for AI/ML studies.
  
  

• Equitable and Ethical AI Integration:

• Lead the documentation, planning, design, building, implementation, and maintenance of data management systems (e.g., data lakes) incorporating fair and ethical AI/ML approaches.

• Research, identify, and apply standardized benchmarks, thresholds, and metrics as appropriate to ensure ethical AI integration.
  
  

• Thought Leadership:

• Conduct literature reviews independently and write reports and presentations to support publications, grant proposals, and the advancement of research projects.

• Provide programming and subject matter expertise to refine the development of new approaches and identify and validate relevant data sets.

• Offer advanced statistical support, including recommendations for data and predictive models, data visualization, validation of existing and proposed models and techniques, and development of new data and predictive models.

• Create new experimental frameworks to collect, analyze, and categorize data.

SECONDARY RESPONSIBILITIES:

• Interdisciplinary Collaboration:

• Collaborate with the software development team, prepare research tools and statistical models for deployment on scalable applications and tools, including dashboards.

• Collaborate with data sets and data science sources within NYU, government agencies, and other research teams outside of NYU to link program data with other health and personnel data to support AI/ML research.
  
  

• Workflow Management:

• Develop and create documentation regar