Social Science Data Scientist

As a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem-solving skills and dedication to build stronger minds and a healthier world.

UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits and natural beauty.

POSITION PURPOSE
The eScience Institute has an outstanding opportunity for a social science researcher with strengths in data-intensive methods to join our team as a Data Scientist. As a member of our core research team, you will participate in expanding campus-wide opportunities at the intersection of data science and social science through collaborative research, consultation, community building, and educational activities. You will also have the opportunity to explore your own independent research agenda to address questions of social significance through the use of data, data-intensive methods, and computation. The eScience Institute empowers researchers and students in all fields across the University of Washington to answer fundamental and transformative questions. As the hub of data-intensive discovery on campus, we lead a community of innovators in the techniques, technologies, and best practices of data science.

Data Scientist roles in the eScience Institute are full time, permanent (not term-limited), appointments where you can build a career with advancement opportunities and a rich set of professional development and mentorship opportunities.

The values of diversity, equity and inclusion are integral to the success of our research enterprise and are embedded in the culture of who we are as an institution and employer. The eScience Institute shares President Cauce’s commitment to combat inequities and racism in higher education and research.

Data Scientists in the eScience Institute provide guidance and expertise to the University of Washington community, including students, post-docs, staff and faculty on the best-practices for, and appropriate application of, data science methods. In addition, they have the opportunity to build their own independent research agenda. These interactions are often structured around a set of programmatic and thematic activities that are core to the eScience Institute mission, which include: Data Science for Social Good (DSSG) program, Data Science Incubator, Data Science Office Hours, and other university wide offerings. To approach complex societal challenges, In the DSSG program teams take a multi-dimensional approach that integrates data science techniques, ethical thinking, and stakeholder engagement to generate real-world benefits. Student Fellows work on interdisciplinary teams led by project leads from academia, nonprofits, and government, along with data scientists at the eScience Institute who offer technical expertise and guidance.

This position requires an individual who is interested in continuous learning opportunities in a higher education research environment. The ideal candidate will have substantive training or experience in the social sciences, digital humanities, linguistics, education or related disciplines and a passion for working to address societal problems through the use of data, data-intensive methods, or computation. The eScience Institute is a highly interdisciplinary environment and our work involves communicating and collaborating across varied disciplinary, theoretical, and methodological traditions. You will be joining a team that is respected across campus for their abilities to work with other researchers in both support and leadership roles. The eScience Institute highly values open science. This includes open-source software development, engaging in open data practices, and using best practices for research reproducibility. As a member of the team of 15+ data scientists and researchers in the eScience Institute, you will have the opportunity to have a substantial impact on the development of data science research in the social sciences at the University of Washington and beyond. The duties and responsibilities that impact the University of Washington include working with students, post-docs, staff and faculty to help them understand, adopt and engage in data science in a variety of informal and formal education, research and community building settings and activities. In addition, data scientists in the eScience Institute build and manage their own research programs.

DUTIES AND RESPONSIBILITIES

Programmatic Support
Mentor teams in the Data Science for Social Good program.
Participate as needed and interest arises in other core programs of the Institute, such as the Data Science Incubator, Software Carpentry, Hack Weeks, etc.
Hold open office hours for students, faculty, staff and post-docs.

Organizational Service
Participate in core team meetings and activities.
Serve on standing and/or ad hoc teams such as hiring committees, equity team, etc.
Fostering and building research collaborations with other researchers at UW.

Independent research
Develop a research program rooted in applications of data intensive and data science methods to a social science area.

MINIMUM REQUIREMENTS
PhD in social science field or relevant research equivalence experience.
Two years of experience planning, implementing and assessing the efficacy of data science techniques for studying social science questions, these years of experience may derive from graduate research.

Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.

ADDITIONAL REQUIREMENTS
Commitment to working with open science methodologies and reproducibility.

DESIRED QUALIFICATIONS
Demonstrated commitment to valuing diversity and contributing to an inclusive working and learning environment.
Previous experience teaching or training others.
Previous experience using R.
Previous experience working with open source software workflows for social science.
Previous experience working with researchers from a range of disciplinary backgrounds.
Demonstrated experience in software engineering and/or advanced statistical methods.