Anthony Suen, Data Science Fellow

Closed (1) Data Science Discovery Program

Applications for fall 2021 are now closed for this project.

PLEASE NOTE for this project ONLY:
You do not need to submit an application through URAP! Please apply directly to the Data Science Discovery Program, the instructions are below. If you are accepted, you will be received research credit through a a separate course listing (not URAP). Please note: You will be allowed to apply to up to three Discovery projects, and application to Discovery projects does not count against the maximum of 3 allowed URAP applications.
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We are thrilled to announce the opening of this semester's Data Science Discovery application (http://dsdiscovery.org/)! The Data Science Discovery program (https://data.berkeley.edu/research/discovery-program-home) connects undergraduates with hands-on, team-based opportunities to contribute to cutting-edge data research projects with on and off-campus partners. If you want to work on data science projects that will have an impact on the world around you, submit your application by August 22nd.

Prerequisites: Data 8

Resources:

Project list and application: http://dsdiscovery.org/
Check out descriptions and expectations for this semester’s projects.

Application deadline: August 22nd, 11:59pm PT

Next Steps: Project Partners will reach out to students to schedule interviews and make offers. Teams will be finalized by September 8th.

Academic Credit: If you accept an offer with a Discovery project you will be automatically registered for URAP research units (one unit is available for every 3 hours of work you do). More details on receiving URAP credit will come after the application deadline.

Questions: ds-discovery@berkeley.edu

Note: Please apply at the above link (http://dsdiscovery.org), NOT through the URAP portal.

Roles: Data analysis, data visualization, data management, machine learning, etc.

Qualifications: Data 8 is a prereq, and CompSci 61A is a recommended course. For more advanced projects, Data 100 and CompSci 61B are preferred.

Weekly Hours: to be negotiated

Off-Campus Research Site: Remote

Related website: http://dsdiscovery.org/
Related website: https://data.berkeley.edu/research/discovery-program-home

Closed (2) Data Science Education Program Student Teams Opportunities

Closed. This professor is continuing with Spring 2021 apprentices on this project; no new apprentices needed for Fall 2021.

DSEP teams work with faculty to create open-source materials for lectures, labs, and homework. Some analyze student experience data to make informed decisions that will shape courses and programs across campus, and some integrate issues of ethics into the Berkeley data science program and community. Hone your skills as a data scientist and build a portfolio while making an educational impact across campus!

Use the following link to apply:
https://docs.google.com/forms/d/e/1FAIpQLSdfWnd6udVB-ccVo8qq97vAaniqaNT_TQftWOdJt1Nqb65mGA/viewform

Note:
--Applicants who do not apply through our Google Form will not be considered.
--Applying through URAP is mandatory if you apply to GoodlyLabs projects; otherwise, it is optional.
--We are looking to fill 30-35 curriculum developer roles ASAP. We will consider these applications on a rolling basis, especially if curriculum development is marked as your first choice.

Roles: Jupyter notebooks development, data analysis, data visualization, etc.

Qualifications: Data 8 is required. Data 100, CompSci 61A, and CompSci 61B are preferred.

Weekly Hours: to be negotiated

Related website: https://data.berkeley.edu/academics/resources/student-opportunities

Closed (3) Data Science Peer Advising Opportunities

Closed. This professor is continuing with Spring 2021 apprentices on this project; no new apprentices needed for Fall 2021.

The Data Science Peer Advisors provide in-person and online academic advising to students interested in pursuing the L&S Data Science major. Peer Advisors also develop info sessions and tutorials to inform intended Data Science students about enrollment and prerequisites, and have the opportunity to help improve the undergraduate experience for their peers. Peer Advisors work closely with the Data Science Advising Team and gain exposure to the ins-and-outs of a new and increasingly popular interdisciplinary major.

Use the following link to apply:

https://docs.google.com/forms/d/e/1FAIpQLSebmNg_UPC75KG-LARyRljscowEpsNw4aboqpiDMc7Gpr5J_g/viewform

Notes:
--Applicants who do not apply through our Google Form will not be considered.
--Applying through URAP is mandatory if you apply to GoodlyLabs projects; otherwise, it is optional.

Roles: Peer advising, peer support, event planning, etc.

Qualifications: Must be a declared Data Science major/minor.

Weekly Hours: to be negotiated

Related website: https://data.berkeley.edu/academics/resources/student-opportunities

Closed (4) Division of Data Science and Information Internal Operations Opportunities

Closed. This professor is continuing with Spring 2021 apprentices on this project; no new apprentices needed for Fall 2021.

The Internal Operations interns support the crucial functions of the Division by developing our branding and marketing platform, managing the initiatives that draw all of our student programs together, and creating and maintaining a sense of data science community. Learn the ins-and-outs of a rapidly growing academic organization and make your mark on the largest Data Science education program in the nation.

Use the following link to apply:
https://docs.google.com/forms/d/e/1FAIpQLSebmNg_UPC75KG-LARyRljscowEpsNw4aboqpiDMc7Gpr5J_g/viewform

Note:
--Applicants who do not apply through our Google Form will not be considered.
--Applying through URAP is mandatory if you apply to GoodlyLabs projects; otherwise, it is optional.
--All of these positions are paid.

Roles: Program planning, program coordination, communications, technical support, etc.

Qualifications: Data 8 is required.

Weekly Hours: to be negotiated

Related website: https://data.berkeley.edu/academics/resources/student-opportunities