Data Scientist - Schmidt DataX Project, Princeton University
Do you have a strong background in scientific programming, academic research, and are eager to contribute to groundbreaking research? Do you love to write code and analyze data? Then please consider joining our growing team of data scientists!
Princeton University is building a community of data scientists to work in partnership with its world-renowned faculty and students to help solve data-driven research problems. You will work with faculty in a collaborative, multidisciplinary environment and actively contribute your skills to advance scientific discovery and have access to Princeton's first-class resources, the opportunity to co-author academic publications, to offer short courses and workshops on data science, and to collaborate the larger computational data science community.
Three research areas are of particular interest and led by the Department of Chemistry (catalysis), Department of Computer Science (biomedical data) and Center for Information Technology Policy (technology policy). Prior experience in one of the above areas is an asset. You will be mentored in the relevant research area. These are 3-year appointments offering a very competitive salary and excellent opportunities for growth and career development. The positions are part of the Schmidt DataX project, an initiative made possible by a major gift from Schmidt Futures.
- Integrate with interdisciplinary research teams and creatively develop/apply modern data science, statistics, and machine learning techniques to advance research.
- Coding/algorithmic prototyping of relevant analysis methods, including setting clear goals, measuring progress, and the creation of appropriate documentation.
- Collaborate with, educate, convene, and support a broad community of researchers on campus in how to best leverage data science in their teaching and research. This may include contributing to mini-courses and workshops on data science.
- Communicate results and impact to all stakeholders. This may include presenting research at academic conferences and workshops.
- PhD required in computer science or related discipline or equivalent combination of training, experience, and accomplishments.
- Strong coding/algorithm prototyping skills, and ability to explain and document work.
- Proficiency in one or more of the following: Python, C, C++, SQL
- Experience working in data analysis/statistics/machine learning/scientific computer to address basic research questions; or commensurate achievements
Additional Desired Qualifications:
- Strong problem-solving skills; a passion for answering hard questions with data.
- Preferred background for these areas:
- Catalysis: chemistry
- Biomedical Data: strong computer science experience and machine learning; able to analyze large repositories of biomedical data
- Technology Policy: statistics and machine learning
- The ability to communicate complex ideas to relevant stakeholders.
- Experience in a collaborative, multi-disciplinary research environment
- Eagerness to collaborate with both technical and non-technical colleagues.
- Experience in database design and building data-driven web applications Princeton provides an exceptional work environment that includes a comprehensive set of programs and benefits for you, your spouse or domestic partner, and your family including: competitive health, dental, vision and life insurance; generous vacation and sick leave packages; retirement planning with a generous company match; competitive parental leave; Backup Care Advantage for child or elder care. Access application at https://www.princeton.edu/acad-positions/position/15201. Please include a cover letter (preferred) or writing sample, curriculum vitae, and names and contact information of three references. References will only be contacted if you are a finalist. This position is subject to the University's background check policy.