Research Data Scientist

Full time

Created: May 21, 2018
Davis, California USA
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The UC Davis Data Science Initiative is seeking a full-time Data Scientist to join our team. The Data Scientist will support academic research by designing and implementing practical solutions to data science challenges.

This position involves:

-        Working on numerous, diverse cutting-edge collaborative research projects

-        Providing data science advice and services/support for other projects and researchers

-        Offering workshops to train students, staff, and faculty in data science methods and technologies

-        Developing general, reusable data science infrastructure, methods, software and tools.

The Data Scientist will apply statistical and machine learning methods and other data science techniques to real-world problems to aid data-enabled, multi-disciplinary research. Our Data Scientists are expected to continually learn, share, and problem solve while working with researchers from across the university.


About the DSI

The UC Davis Data Science Initiative (DSI) was founded to promote and support research and training in data-driven discovery across all colleges, schools and disciplines at UC Davis. We facilitate data-enabled research and training at the frontiers of scientific, engineering, social and humanities disciplines. A highly interdisciplinary, cross-university entity, the DSI is housed in the main university Library and serves as a hub for a community of researchers and students from many domains interested in data science and pushing the envelope of research in the digital age. The DSI coordinates data-science training activities, provides consulting and collaborative services for research projects, and conducts novel research in data science. We run training workshops on fundamental and intermediate to advanced data science topics. We run problem-solving “un-seminars”, reading groups, and generally foster community. Our research and training activities span the entire research data pipeline, from data acquisition, management, cleaning, transformation, visualization, and modeling to dissemination/publication and high-performance computing, and involve aspects of data governance, security, privacy and ethics. The DSI is committed to fostering an inclusive environment to promote all members of the university community, including faculty, students and staff from a variety of domains, backgrounds, cultures and personal experiences. For more information, see and


Minimum Qualifications

-        Bachelor’s degree in a data-analytic discipline (e.g., Data Science, Statistics, Computer Science, Mathematics, Engineering, or a data-driven disciplinary field), or equivalent experience, training and education.

-        Experience involving hands-on data science problem solving with real-world, complex (messy!) data sets.

-        Problem-solving and data manipulation skills.

-        Knowledge and experience applying statistical modeling and machine learning methods to real world problems.

-        Knowledge and experience conducting one or more of: Web scraping, static and dynamic visualization, text mining, or natural language processing.

-        Proficiency in a high-level programming language (e.g., R or Python).

-        Experience using advance organizational skills and knowledge to organize, manage, prioritize and work on multiple, dynamic projects; and fulfill assigned tasks and projects including learning new methods and technologies.

-        Interpersonal and communication skills for research, technical and lay audiences.


Preferred Qualifications

-        Advanced degree in a data-analytic discipline, or in a disciplinary field with significant data science background, or equivalent experience/training.

-        Experience working in teams to solve data-driven, interdisciplinary problems.

-        Experience with:

  • SQL and NoSQL database technologies
  • Parallel computing paradigms and technologies for data science.
  • Software development, version control, unit testing, portability.

-        Knowledge of data-driven research, scholarly communication, and the technical and social aspects of the research data lifecycle.

-        Experience developing and leading training and educational activities on data science topics, methods and/or technologies.

-        Experience supervising interns.


How to Apply:

For details see the attached flyer and

Direct applicant link:  

Questions can be directed to


Last updated: Tuesday, May 22, 2018 18:30 UTC

How to apply



Published: Tuesday, May 22, 2018 18:30 UTC