Data Scientist

Princeton University•Princeton, NJ

2d•$125,000 - $138,000•Remote

About The Position

The Accelerator seeks a Data Scientist to bolster its data team and provide insight into the data it collects. The Accelerator at Princeton includes a portfolio of multiple planned independent and intersecting tools. Reporting to the Head of Data Science and Data Engineering, the data scientist will work within the team to help drive data science and data engineering initiatives and collaborations. They will play a crucial role in using data-driven approaches to drive innovation, solve complex engineering problems, and ultimately advance scientific research. They will work on problems that have no precedent and little source material, requiring novel solutions. They will also be responsible for working with the other teams within the Accelerator and its external partners to help foster collaboration and create an incredibly impactful environment for its users. This is a 6-month term role with potential for extension.

Requirements

3+ years of relevant work experience as a frontline data scientist, with a record of building innovative solutions.
Experience working in a remote, agile environment.
Bachelor's degree or equivalent in a relevant field
Strong communication and interpersonal skills to effectively collaborate with researchers in the field, other engineers at various levels of experience, and administrative and leadership team members.
Modern Software Engineering Foundations: agile (Scrum), DevOps, CI/CD, and pair programming, with working knowledge of cloud compute platforms to support collaborative, scalable, and efficient development.

Nice To Haves

Background in engineering principles and familiarity with various engineering disciplines.
Publications in reputable scientific journals or conferences is desirable.

Responsibilities

Work closely with the Accelerator leadership team to align data science initiatives with overarching goals and long-term vision.
Identify and prioritize development projects that benefit from data science methodologies and innovations.
Apply advanced statistical analysis, data mining, and machine learning techniques to analyze complex engineering datasets.
Design, develop, and optimize predictive models, simulations, and algorithms to solve key engineering and scientific challenges.
Drive the development and deployment of data-driven products and solutions, ensuring alignment with strategic goals.
Ensure the accuracy, integrity, and quality of data to be made available through the Accelerator.
Collaborate with data engineering teams to optimize data workflows, enhance data accessibility, and improve performance of modeling systems.
Understand the end-to-end data lifecycle and its effects on machine learning models, actively enhancing and optimizing data pipelines for improved model outcomes.
Ensure the accuracy, integrity, and quality of data to be made available through the Accelerator.
Develop data pipelines, automation systems, and scalable infrastructure for real-time and batch processing.
Work effectively in a modern, professional software and data engineering environment with a strong understanding of Agile concepts and practices.
Stay current with the latest advancements in data science, machine learning, and relevant engineering fields to continuously innovate.
Collaborate with research teams to apply state-of-the-art techniques to ongoing scientific challenges.
Build strong relationships with external partners, driving collaborations that enhance the Accelerator’s scientific impact.