Computing and Information Services (CIS) seeks a talented and motivated Data Science Associate to undertake an ambitious portfolio of interesting projects involving data from across the university. Joining the CIS Data Science Practice (http://brown.edu/cis/data-science), he or she will support data-driven decision making by senior administrators and enhance the universityâ??s research efforts through partnerships with faculty on big data research.
Data-driven decision making
Important decisions that affect Brownâ??s policies, operations and competitiveness are increasingly relying on the availability and interpretation of institutional data. We conduct analyses, build data services, and develop predictive models that help administrators make decisions with better information and greater confidence.
Many Brown researchers already depend on advanced computational methods to store, analyze, interpret and visualize large amounts of data, and these needs are growing as many areas of research, in both the sciences and humanities, become increasingly computational and data-driven. We partner with faculty and researchers to fill key needs in their research groups and labs, helping them to use data more effectively in their research.
Data Science Associates work closely with and learn from senior members of the Data Science Practice, and have the opportunity to refine their data modelling, analysis, and software engineering skills on real-world data and problems.
Please note: a cover letter and resume must be included in all applications to be considered for this position.
This is a two year fixed-term staff position, with the possibility of extension contingent upon available funding.
The grade level of the position will be determined based on the qualifications of the chosen candidate.
Qualifications for Grade 9E position:
A Bachelorâ??s in an area with a technical and computational emphasis and 1 or more years of work or internship experience
Coursework in mathematics, computer science, and statistics is a plus.)
Previous experience with machine learning is preferred.
Expertise in two or more of the following areas: statistics; informatics; data mining, exploration and visualization; data management; software engineering.
Strong intrinsic motivation and an eagerness to learn and apply new skills.
Effective at communicating with audiences whose technical backgrounds vary widely.
Ability to work well both independently and collaboratively, and to manage multiple projects with competing priorities and deadlines.
Additional Qualifications for 10E:
Advanced degree or PhD in a computationally intensive field (e.g., natural sciences, life sciences, computer science) preferred.
2 - 3 years of work experience including post doc or research assistanceship.
All offers of employment are contingent upon a criminal background check and education verification satisfactory to Brown.
Recruiting Start Date:
Job Posting Title:
Data Science Associate
Office of CIO
Fixed Term (Fixed Term)
Scheduled Weekly Hours:
Please note that in order to be considered an applicant for any staff position at Brown University you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Brown University is committed to fostering a diverse and inclusive academic global community; as an EEO/AA employer, Brown considers applicants for employment without regard to, and does not discriminate on the basis of, gender, sex, sexual orientation, gender identity, national origin, age, race, protected veteran status, disability, or any other legally protected status.
Located in historic Providence, Rhode Island and founded in 1764, Brown University is the seventh-oldest college in the United States. Brown is an independent, coeducational Ivy League institution comprising undergraduate and graduate programs, plus the Alpert Medical School, School of Engineering, Executive Master of Healthcare Leadership and the IE Brown Executive MBA.