Department Purpose

The Office of Grand Challenges provides dedicated leadership and facilitation for current and future research, education, and public service activities focused on UC Davis campus priorities for action to address the world’s wicked problems (herein “Grand Challenges”), including, but not limited to: emerging health threats, other obstacles to individual and

community wellness, climate change, social and environmental justice, environmental degradation, and food systems. Grand Challenges is also planning a new built environment, conceived of as a special space that will be an ideal site for Grand Challenges programs and a focal point for transdisciplinary collaboration campus-wide.

Job Summary

The Data Scientist will provide advanced analytics and Artificial Intelligence/Machine Learning (AI/ML) expertise to the Grand Challenges Data Science team, and under general direction of the Grand Challenges Vice Provost, will support strategically important computational projects within the UC Davis Institute for Pandemic Intelligence (IPI). They will contribute to the SpillOver: Viral Risk Ranking project (aka SpillOver), which explores and directly compares hundreds of viruses of wildlife-origin to identify viruses with the highest risk of zoonotic transmission from wildlife to humans and spread in human populations. They will enhance the SpillOver application by applying appropriate machine learning methods to increase the breadth of data incorporated in virus risk rankings and optimize the rankings against the large volumes of new and disparate data becoming available from ongoing viral discovery efforts. The updated rankings will help identify the most important viruses for pre-emptive development of vaccines, thereby contributing to epidemic and pandemic preparedness against these pathogens.

The ideal candidate will have knowledge of applying statistical and machine learning methods to real-world problems and will be expected to continually learn, share, and problem solve while working with the research team members. They will develop, test, and document methods, software and tools and contribute to the development of peer-reviewed publications and conference presentations on the updated risk rankings.

POSITION INFORMATION

PHYSICAL DEMANDS

• Ability to sit and work at a computer for extended periods of time

WORK ENVIRONMENT

• 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

MINIMUM QUALIFICATIONS

Minimum Education/Experience:

• Advanced degree in a data-analytic discipline (e.g., Data Science, Statistics, Computer Science, Mathematics, Engineering, or a data-driven disciplinary field), or Bachelor’s degree with at least four years of equivalent experience.
• Advanced knowledge and demonstrated experience with AI and statistical methodologies (e.g., classification and ranking algorithms, deep learning, NLP, text mining, mixed models, network analysis, Bayesian methods, model selection, hyper-parameterization, and model tuning).
• Demonstrated experience as a computational scientist in any scientific domain with hands-on computational problem-solving skills and application of statistical/ML methods to real-world problems.

Minimum Knowledge, Skills, and Abilities (KSA) :

• Proficiency in R or Python and associated ML libraries such as caret, xgboost, Pytorch, TensorFlow, spaCy, etc.
• Demonstrated knowledge of software development best practices such as version control, continuous integration, testing, and documentation.
• Ability to work both independently and as part of an interdisciplinary team, including collaborating with other programmers on code projects and their documentation.
• Strong organizational and project management skills, as well as strong written and verbal communication skills.

PREFERRED QUALIFICATIONS

Preferred Education/Experience:

• Master’s or PhD degree in a data-driven disciplinary field with significant data science background, or equivalent training and experience.
• Experience with ML Ops , cloud computing (AWS, Google Cloud, etc), containerization tools (e.g. Docker) and parallel computing paradigms and technologies for data science.
• Experience with relational and non-relational database management systems.

SPECIAL REQUIREMENTS

Background Check

This position is a critical position and subject to a background check. Employment is contingent upon successful completion of background investigation including criminal history and identity checks.

Diversity, Equity, Inclusion and Belonging

At UC Davis, we’re solving life’s most urgent challenges to bring a fuller, healthier, and more resilient world within reach. We grow from every challenge we take on and we don’t just maintain - we improve.

We recognize that creating an inclusive and intellectually vibrant organization means understanding and valuing both our individual differences and our common ground. The most comprehensive solutions come from the most diverse minds and you belong here.

As you consider joining UC Davis, please explore our Principles of Community, our Clinical Strategic Plan and strategic vision for research and education, and our latest efforts to outgrow the expected.

The University of California is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.