The UC Davis DataLab is seeking a full-time Research Data Scientist to join our team. The Research Data Scientist will support academic research by designing and implementing practical solutions to data science challenges. The Data Scientist will support academic research across the university by designing and implementing practical solutions to data science challenges. This position is responsible for working on numerous diverse, cutting-edge, collaborative research projects, providing data science consultation and services/support for other projects and researchers, offering workshops to train students, staff, and faculty in data science methods and technologies, and developing general, reusable data science infrastructure, methods, software and tools. The ideal candidate will have knowledge of applying statistical and machine learning methods to real-world problems and will be responsible for applying statistical and machine learning methods and other data science techniques to real-world problems. The ideal candidate will also be expected to continually learn, share, and problem solve while working with researchers and students from across the university. This is a contract appointment that ends two years from the date of hire with the possibility of extension or conversion to a career position based on performance and available funding.
About DataLab:
DataLab promotes and facilitates data-enabled research and training at the frontiers of scientific, engineering, social and humanities disciplines, both applying existing and developing new methods in order to solve previously unsolved problems. A highly interdisciplinary, cross-university entity, the DataLab serves as a hub for a community of researchers and students from many domains who are interested in data science and pushing the envelope of research in the digital age. The DataLab provides advice and consultation, short-term services, and longer-term collaborations. It runs training workshops on many data science topics primarily at the intermediate and advanced levels. It holds problem-solving un-seminars”, learning clusters, co-sponsors symposia and conferences, and generally fosters community. While the diverse efforts engaged in by the DataLab require a range of programming languages and experience, the common programming languages of the unit are R and C. For more information, see http://DataLab.ucdavis.edu and https://www.ucdavis.edu/.”
The UC Davis Library is a hybrid digital and physical work environment that values collegiality, respect for one another, and ongoing personal and professional development.The physical facilities of the library comprise the Peter J. Shields Library in Davis and the Blaisdell Medical Library at the UC Davis Health campus in Sacramento. For more information about the library, visit http://library.ucdavis.edu/about.
Duties and Responsibilities:
- Provide practical data science support for research projects including applying modern statistical modeling, machine learning, data acquisition, cleaning, visualization, and text mining techniques
- Communicate and work with various types of scholars and researchers with different expertise and domain knowledge
- Contribute to grant proposal development
- Take an active leadership role in assigned projects, utilizing the prescribed project management methods, related processes, and standards
- Develop, maintain, and publish Open Source software for general data science problems
- Develop and (co-) lead training and educational activities in areas of expertise;
- Collaborate with personnel at the DataLab to ensure knowledge transfer and best practices cross- pollination
- Engage with and support the DataLab and university’s data science community, which includes providing office hours and consultations, as well as mentoring and training students and working with relevant university units
- Assist with other duties as assigned, including continued professional development in data science
Minimum Qualifications:
- Master’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 data sets
- 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
Minimum Knowledge, Skills, and Abilities:
- 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 R or Python
- Interpersonal and communication skills for research, technical and lay audiences
Preferred Education/Experience:
- PhD 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
- Experience with parallel computing paradigms and technologies for data science
- Experience with software development, version control, unit testing, portability
- Experience developing and leading training and educational activities on data science topics, methods and/or technologies
- Experience supervising interns
Preferred Knowledge, Skills, and Abilities:
- Knowledge of data-driven research, scholarly communication, and the technical and social aspects of the research data lifecycle
Work Environment: Maintain a work schedule during core business hours (working hours will vary from 8:00 am – 6:00 pm, Monday through Friday) with occasional irregular shifts, weekends, holidays and evenings on short notice to meet operational needs, international conference calls, and occasional deadlines or emergency needs as necessitated by project launches, major events, funding deadlines and IT systems availability. Work in an open office environment with multiple interruptions. Occasional travel to off-campus locations. Infrequent out-of-state and/or international travel for training, conferences, and project work. Overnight stays may be required. This is a critical position that includes handling of potentially sensitive data types and is subject to a background check. Employment is contingent upon successful completion of background investigation including criminal history and identity check.
The Smoke and Tobacco Free Environment policy is intended to provide a healthier, safer, and more productive work and learning environment for the entire UC community. The University of California prohibits smoking and tobacco use at all University owned or leased properties, or facilities operated by UC staff or faculty. Smoking and tobacco use are strictly prohibited in indoor and outdoor spaces, parking lots, residential space, and University vehicles.https://ucdavispolicy.ellucid.com/documents/view/271
Physical Demands: Standing or sitting at a computer workstation for extended periods of time, operating and occasionally moving computer and peripheral equipment and other supplies (up to 30 lbs); communicate in person, telephone and e-mail, and other online services; understanding and interacting with program output and a variety of operating systems and computer displays.
Principles of Community: UC Davis is a diverse community comprised of individuals having many perspectives and identities. We come from a multitude of backgrounds and experiences, with distinct needs and goals. We recognize that to create an inclusive and intellectually vibrant community, we must understand and value both our individual differences and our common ground. The UC Davis Principles of Community is an aspirational statement that embodies this commitment, and reflects the ideals we seek to uphold. https://diversity.ucdavis.edu/principles-community
The link to apply and more information to come, so check back soon! Please address any questions to datalab@ucdavis.edu.