Research Data Analyst 1
Doerr School of Sustainability, Stanford, California, United States
New
Information Analytics
Post Date 11 hours ago
Requisition # 106891
This position has been deemed critical by the Stanford Doerr School of Sustainability Dean's Office and is exempt from the hiring pause.
This position is based on Stanford's main campus with consideration given to the option for a hybrid work schedule (partially onsite and offsite), subject to operational need. Interested candidates must include a resume and cover letter to be considered for this position.
This is a one-year fixed term full time position with the possibility of renewal, dependent on funding availability and programmatic need.
Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment VISA.
About Us
The Stanford Doerr School of Sustainability strives to create a future when humans and nature thrive in concert and in perpetuity. The school is made up of a three-part structure to drive global impact: Our academic departments and programs educate students and create new knowledge across areas of research that are crucial for advancing the long-term prosperity of the planet and people; Institutes bridge scholarship at Stanford and beyond, bringing multiple viewpoints to bear on urgent challenges; The Sustainability Accelerator drives new policy and technology solutions through a worldwide network of partners who work with our teams to develop solutions at a global scale. The school is dedicated to creating and supporting a community with the richness of experience and background needed to create solutions that benefit all people, particularly those most affected by environmental damage and climate change.
For more information on the school, clickhere.
Environmental Social Sciences at the Stanford Doerr School of Sustainability is a new and rapidly growing department. The mission of the department is to shed light on the causes of humanity's sustainability challenges, to design and evaluate potential business strategies, public policies, and behavioral interventions to meet these challenges, and to educate future scholars and leaders who will further our vision of understanding and solving these challenges.
The Global Policy Laboratory (GPL) at Stanford University 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, Professor of Environmental Social Sciences 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. The project is digitizing, combining, and applying machine learning to analyze millions of historical aerial photographs collected around the world.
Your Responsibilities will include:
GPL and the AHP are looking for an outstanding Data Scientist with data engineering expertise, ideally with a background in machine learning for computer vision, remote-sensing, and/or applied econometrics. The Data Scientist will also be responsible for the development of solutions to improve the visual quality of the final output. The role will involve gathering, analyzing, and interpreting research data according to established statistical methods. The ideal candidate will be highly proficient in Python and have experience in quantitative research and machine learning techniques (specifically in Computer Vision and Image Processing, including remote sensing). The Data Scientist will work as a core member of a growing team, which includes research staff, students, post-doctoral researchers, and faculty.
The Data Scientist will be responsible for scaling up and maintaining the data pipeline. The Data Scientist will also work with team members to identify priorities and set project objectives, develop models for application to the data and assist in preparing materials to help communicate findings.
Oversee development of project's data pipelines.
Prioritize and extract data from a variety of sources such as notes, survey results, reports, and laboratory data, and maintain its accuracy and completeness.
Determine additional data collection and reporting requirements.
Oversee and monitor regulatory compliance for utilization of the data.
Adapt and improve on existing infrastructure for future project needs (e.g., scaling up to accommodate more data, improve data quality).
Analyze problems, experiment with suitable architectures, design and deploy solutions.
Manage the outsourcing of manual data processing tasks with third-party vendors.
Develop materials and visualize data to communicate results.
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The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
To be successful in this position, you will need:
Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.
Extensive knowledge in machine learning, particularly in Computer Vision and Image Processing.
High proficiency in Python.
Experience with Python machine learning and numerical libraries such as Scikit-learn, Numpy, Pandas, PyTorch, or TensorFlow.
Good understanding of inferential and descriptive statistics.
Ability to work under deadlines with general guidance.
Excellent organizational skills and demonstrated ability to complete detailed work accurately.
Effective oral and written communication skills.
Ability to work effectively with multiple internal and external customers.
Ability to take a leadership role on projects and with users/clients.
In addition, our preferred qualifications include:
Working knowledge on developing and maintaining databases (SQL/relational and non-relational).
Experience in remote sensing or spatial data analysis.
Working knowledge of statistical programs (e.g., Stata, R).
Experience using cloud computing platforms such as Google Cloud Platform.
Experience in orthorectification.
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- Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job.
The expected pay range for this position is $80,148.00 to $99,773.00 per annum.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
How to Apply
We invite you to apply for this position by clicking on the "Apply for Job" button.
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting acontact form.
Stanford is an equal employment opportunity and 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, protected veteran status, or any other characteristic protected by law.
Additional Information
Schedule: Full-time
Job Code: 4751
Employee Status: Fixed-Term
Grade: G
Requisition ID: 106891
Work Arrangement : Hybrid Eligible
