The Violence and Inequality Project (VIP) is seeking a full-time Programmer/Data Scientist. The ideal candidate will have a strong background in programming in R and Python, particularly in the context of simulation and modeling. Any experience programming with Julia would be a bonus, although it is not necessary. Candidates should be interested in applying computational techniques to the study of interventions designed to confront violence. The Programmer is expected to work full-time, and will work closely with Principal Investigator, Patrick Sharkey.
This is a one-year term limited position, with possibility of extension conditional on funding. The anticipated start date for this position will be in January 2026.
• Design, develop, and implement agent-based models (ABMs) for various applications, including social, economic, environmental, and biological systems.
• Write clean, efficient, and well-documented code to simulate agent behaviors and interactions within complex systems.
• Validate and refine models through rigorous testing and calibration against real-world data.
Optimize model performance and scalability to handle large-scale simulations.
• Assist in the interpretation and presentation of simulation results to inform decision-making processes.
• Work with other team members to convert code developed in R into Python and Julia.
• Collaborate with cross-functional teams, including data scientists, domain experts, and stakeholders, to define model objectives and parameters.
• Stay up-to-date with the latest advancements in agent-based modeling, simulation techniques, and relevant programming languages or tools.
• Contribute to the publication of research findings in scientific journals or industry reports, where applicable.
ESSENTIAL Minimum Required Knowledge, Skills, Competencies, and Abilities
• Bachelor's degree or equivalent in Computer Science, Computational Science, Engineering, Mathematics, or a related field or post-doctoral candidate.
• Minimum 1-year experience as a Data Scientist or equivalent experience (e.g. graduate school or industry experience).
• Substantial experience coding in Python and R.
• Strong understanding of algorithms, data structures, and computational theory.
• Experience with data analysis and visualization tools to interpret simulation results.
• Ability to work independently and collaboratively in a multidisciplinary team environment.
• Demonstrated interest in applying computational methods to the study of public policy, and particular interest in the challenge of gun violence.
• Excellent problem-solving skills and attention to detail.
• Strong written and verbal communication skills.
PREFERRED Knowledge, Skills, Abilities, Experience, and Other Education
• Master's degree in Computer Science, Computational Science, Engineering, Mathematics, or a related field or post-doctoral candidate.
• Experience with machine learning techniques and their integration into agent-based models.
• Familiarity with parallel computing and cloud-based simulation environments.
• Knowledge of specific domains such as epidemiology or social sciences.
• Familiarity with web-scraping and HTML.
• Proven experience in developing agent-based models or similar simulation models.
• Demonstrated interest in applying computational methods to the study of public policy, and particular interest in the challenge of gun violence.
Princeton University is an Equal Opportunity 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.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.