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Job ID: 155594

Data Scientist (6256U) 16096
University of California, Berkeley

Date Posted Mar. 9, 2021
Title Data Scientist (6256U) 16096
University University of California, Berkeley
Berkeley, CA, United States
Application Deadline Open until filled
Position Start Date Available immediately
  • Professional Staff
  • Public Safety
    Information Technology

Data Scientist (6256U) 16096

About Berkeley

At the University of California, Berkeley, we are committed to creating a community that fosters equity of experience and opportunity, and ensures that students, faculty, and staff of all backgrounds feel safe, welcome and included. Our culture of openness, freedom and belonging make it a special place for students, faculty and staff.

The University of California, Berkeley, is one of the world's leading institutions of higher education, distinguished by its combination of internationally recognized academic and research excellence; the transformative opportunity it provides to a large and diverse student body; its public mission and commitment to equity and social justice; and its roots in the California experience, animated by such values as innovation, questioning the status quo, and respect for the environment and nature. Since its founding in 1868, Berkeley has fueled a perpetual renaissance, generating unparalleled intellectual, economic and social value in California, the United States and the world.

We are looking for equity-minded applicants who represent the full diversity of California and who demonstrate a sensitivity to and understanding of the diverse academic, socioeconomic, cultural, disability, gender identity, sexual orientation, and ethnic backgrounds present in our community. When you join the team at Berkeley, you can expect to be part of an inclusive, innovative and equity-focused community that approaches higher education as a matter of social justice that requires broad collaboration among faculty, staff, students and community partners. In deciding whether to apply for a position at Berkeley, you are strongly encouraged to consider whether your values align with our Guiding Values and Principles, our Principles of Community, and our Strategic Plan.

Application Review Date

The First Review Date for this job is: March 22, 2021

Departmental Overview

The Global Policy Laboratory (GPL) at UC Berkeley is an interdisciplinary research group that integrates physical science, social science, and data science to answer questions that are central to managing planetary resources---such as the economic value of the global climate, the effectiveness of treaties governing the oceans, how the UN can fight wildlife poaching, and whether satellites and AI can be combined to monitor the entire planet in real time. The GPL team's research has been published in Nature, Science, and PNAS, their findings have been covered in thousands of news outlets, and the team regularly interacts with policy-makers at federal and international levels. The lab is directed by Solomon Hsiang, Chancellor's Professor of Public Policy and a National Geographic Explorer.

The Aerial History Project (AHP) is a multi-year research initiative joint between GPL and colleagues at Stockholm University. The project aims to better understand how economic development and environmental change interact, for example, by understanding how climate change is affecting human migration in Africa, how natural disasters affect economic development in the Caribbean, and studying whether deforestation can be forecast on multi-decadal time scales. The project is digitizing, combining, and applying machine learning to analyze millions of historical aerial photographs collected around the world. The Aerial History Project was awarded an AI for Earth Innovation grant by Microsoft and National Geographic.

  • Serve as the project's technical lead and oversee development of project's data pipelines
  • Adapt and improve on existing infrastructure for future project needs (e.g. scaling up to accommodate more data)
  • Analyze problems, experiment with suitable architectures, design and deploy solutions
  • Manage the outsourcing of manual data processing tasks on crowdsourcing platforms (e.g. Mechanical Turk)
  • Develop materials to communicate results
  • Other duties as assigned

Required Qualifications
  • Background in computer science, statistics, data science, econometrics or any other quantitative discipline
  • Extensive knowledge in machine learning, particularly in Computer Vision and Image Processing
  • Highly proficient in Python
  • Experience with Python machine learning and deep learning libraries such as Scikit-learn, Numpy, Pandas, PyTorch, or TensorFlow
  • Good understanding of inferential and descriptive statistics
  • Working knowledge of using statistical programs (e.g. Stata, R, Matlab)
  • Bachelor's degree in computer science, statistics, engineering, economics, data science, or related quantitative fields, and/or equivalent experience/training.

Preferred Qualifications
  • Prior experience in remote sensing or spatial data analysis
  • Experience in using cloud computing platforms such as Microsoft Azure, AWS
  • Experience in data visualization using JavaScript libraries
  • Master's degree in computer science, statistics, engineering, economics, data science, or related quantitative fields, and/or equivalent experience/training.

Salary & Benefits

Hourly rate will be commensurate with experience.

For information on the comprehensive benefits package offered by the University visit:

How to Apply

Please submit your cover letter and resume as a single attachment when applying.

Other Information

This is a full-time, 2-year contract with the possibility for renewal based on funding.

Equal Employment Opportunity

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. For more information about your rights as an applicant see:
For the complete University of California nondiscrimination and affirmative action policy see:

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