Research Data Scientist

The Research Data Scientist will work as a technical research staff member at the DSI and report to Prof. Pedram Hassanzadeh, with the primary responsibility of research focused on DSI's efforts at the intersection of AI, Data, and Climate. The Research Scientist will collaborate with the AICE and Climate Extremes Theory and Data group and work directly with Prof. Pedram Hassanzadeh to advance AI weather forecasting across scales, from short- and medium-range to subseasonal-to-seasonal (S2S) predictions. The Research Data Scientist will help lead forecast projects of interest to the Human Centered Weather Forecasts (HCF) Initiative at the Institute for Climate and Sustainable Growth, closely collaborating with a growing multidisciplinary team, including Prof. Michael Kremer (Economics) and Amir Jina (Public Policy), and in conjunction with international efforts at the Development Innovation Lab (DIL). The HCF initiative's projects aim to innovate on and evaluate weather forecasts that can target what citizens on the ground need to know, leveraging the power of artificial intelligence.

This position will involve working with low- and middle-income countries to disseminate forecasts, test their effectiveness, refine based on user feedback, and scale them up through training national meteorological services members and co-developing tools to use and evaluate AI weather forecasts. This role reports to Professor Pedram Hassanzadeh, Faculty Director of the AI for Climate initiative at the DSI.

Work on these topics involves collaborations with leading experts in atmospheric science and AI from the University of Chicago and other institutions. The close partnership with economists and public policy experts at DIL accelerates the translation of the outcome of this work to significant societal impact. In addition to being part of the dynamic AICE and DIL communities, these researchers will benefit from major AI and climate-related activities at the University of Chicago, including the Data Science Institute, the Institute for Climate and Sustainable Growth, and the AI Science Initiative, as well as those at the Argonne National Lab.

Responsibilities

• Delineates new directions of research and executes research and operational milestones in collaboration with principal researchers, research professionals, and other partners. This includes developing long-range plans for research projects and coordinating with principal researchers.
• Supervises the operational deployment of forecasting monsoon and other weather events across scales. Manages hiring in support of the operational forecasting pipeline.
• Participates in the preparation and writing of grant applications and reports as part of larger fundraising initiatives, and co-authors/authors scientific research manuscripts. Provides peer review of grant applications and scientific manuscripts.
• Leads conversations and negotiations with stakeholders to plan, design, and execute collaborations. Establish strong working relationships with and represent the human- centered weather forecasts initiative in meetings with high-level policymakers, funders, nonprofit leaders, and business executives on the global stage.
• Coordinates and conducts weather data acquisition and cleaning necessary for model development.
• Presents work in scientific journals and meetings.
• Contributes unique insights to project management, communication, and research direction for subseasonal-to-seasonal model development.
• Trains and mentors DSI research personnel working on weather and climate applications.
• Has a deep understanding of methods to analyze complex data sets for the purpose of extracting and purposefully using applicable information. May develop and maintain infrastructure that connects data sets.
• Guides staff or faculty members in defining the project and applies principals of data science in manipulation, statistical applications, programming, analysis and modeling.
• Performs other related work as needed.

Minimum requirements include a college or university degree in related field.

Work Experience:

Minimum requirements include knowledge and skills developed through 5-7 years of work experience in a related job discipline., * Ph.D. in Environmental Science, Climate Science, Atmospheric Science, Engineering, Statistics, Applied and Computational Mathematics, Physics or related STEM field.

Experience:

• Strong background and established track record in environmental science, weather forecasting, or climate modeling/dynamics.
• Experience with high-performance computing and analysis of large datasets.

Technical Skills or Knowledge:

• Environmental data analysis, weather forecasting data, and models.
• Strong programming and numerical skills.
• Familiarity with theoretical and practical aspects of scientific deep learning.
• Strong communication skills.

Preferred Competencies

• Ability to work both independently and as part of a multidisciplinary team.
• Ability to lead an interdisciplinary team.
• Ability to work in a fast-paced environment.
• Strong scientific publication record in peer-reviewed journals and conferences in the areas of environmental science, data science, and weather forecasting.

• This position is located in Washington, D.C. and is eligible for a hybrid work schedule with four (4) days remote and one (1) day onsite.
• Business travel to the Hyde Park campus may be required approximately 25% of the time (typically once a month for a week).

The University of Chicago Data Science Institute (DSI) is a collaboration of scholars, researchers, educators, and practitioners pursuing the methodological, societal, and domain-oriented challenges of our increasingly data-centric world. The DSI is a research center setting the intellectual agenda for the field and an innovator and provider of data education at the undergraduate, graduate, and professional levels. Integral to DSI's success includes the rewarding engagement outside the walls of the University through meaningful partnerships with industry, government, and the community. AI for Climate (AICE), an initiative of the Data Science Institute and the Institute for Climate and Sustainable Growth, aims to accelerate and transform climate research, focusing on both scientific advances and societal impacts. The initiative brings together an interdisciplinary group of scientists to adapt AI methods to develop novel tools, such as physics-informed climate and weather predictive models, and trustworthy datasets for training and analysis. Its work aims to improve prediction capabilities and understanding of climate physics, develop quantitative models for the socioeconomic impacts of climate change, and create new climate adaptation and mitigation strategies.