Princeton University

Data Scientist - Schmidt DataX Project

Princeton University, United States

Princeton, NJ, United States

Do you want to apply your data science and computational skills to exciting new research problems? Do you have a background in research but love to write code and analyze data? If so, then we have an exciting opportunity for you.

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. You will 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 with, and learn from, the larger computational data science community

Three research areas are of particular interest. Catalysis: led by the Department of Chemistry; Biomedical Data Science: led by the Department of Computer Science; Technology Policy: led by the Center for Information Technology Policy. Prior experience in one of the above areas is an asset but is not required. You will be mentored in the relevant research area. If you have a strong background in scientific programming, academic research, and are eager to contribute to groundbreaking research, you have the right skill set. 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.

Responsibilities:

  • 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.

Required Qualifications:

  • PhD required in computer science or related discipline; or equivalent combination of educational training, relevant 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 computing to address basic research questions; or commensurate achievements.

Additional Desired Qualifications:

  • Strong problem-solving skills; a passion for answering hard questions with data.
  • 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/13062. 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.

Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. This position is subject to the University’s background check policy.

Please apply via recruiter’s website.

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