The OIT Data & Analytics Fellowship Program is an 18-month program that provides recent graduates a unique opportunity to develop and apply data analytics in the use of institutional data to support Duke’s educational and research mission. The fellowship is a project- and team-based learning experience, in a professional setting, where teams work on strategic and operational projects in a variety of research and administrative areas. Fellows will join the Duke Data & Analytics Practice as core team members and gain real-world experience contributing on high-impact and innovative data engineering and data & analytics projects.

Program Details

Fellows will apply advanced data analytics tools, possibly including advanced data management, machine learning, statistics, and big data methodologies. While learning they will be expected to develop and use their critical thinking, creativity, and analytic skills to contribute to cross organizational and interdisciplinary projects.

Over the course of the 18-month program, fellowship experiences will include:

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  • Involvement in project management, cross-functional team collaboration, and enterprise software development
  • Mentorship from members of the Data & Analytics team
  • Training on specific analytical methods and tools
  • Attendance and presentations at professional and academic meetings
  • Application of best practices in data engineering and analytics
  • Data visualization production and presentation for stakeholders and senior leadership, and
  • Partnerships with subject matter experts, clients, and stakeholders. 

Upon completion of the program, Fellows will have demonstrated foundational data engineering and data science skills, including:

  • Hands-on experience with relational databases, advanced data modeling, and enterprise-scale SQL development and execution
  • Data engineering and software development fundamentals and best practices, including data pipeline implementation through directed acyclic graph (DAG) models, automated CI/CD deployments, and collaborative enterprise software development
  • Data exploration, data visualization, and data storytelling, with principal contributor responsibilities as part of high-impact Duke data analyses and studies with operational, institutional, and academic offices across Duke University 
  • Upon acceptance to the program, fellowships begin in the first summer with Data Analytics onboarding along with supported mentoring experience as Code+ project managers. While serving as a project manager, the fellows will demonstrate team leadership, apply agile frameworks including scrum, and support delivery management
  • Fellows serve as principal contributors to Data & Analytics engagements, with structured professional development across the key learning objectives identified above. They will continuously develop their analytic and quantitative skills and apply academic theory from the classroom to high-impact institutional scenarios using leading-edge data management and data analytics tools

Fellows will earn a competitive salary with support for additional professional development opportunities, including cloud certification through Microsoft Azure partnerships, Machine Learning, and opportunities for additional professional development with OIT Information Technology Security, Threat Intelligence, and Information Systems and Automation.

Upon completion of the fellowship, participants will be well-positioned for key permanent roles within OIT, and support and guidance will also be provided for advancing leadership careers both within Duke as well as with external partnerships. 

Who should apply?

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This is a full-time position and is only open to recent recipients of a bachelor’s degree. 

  • Candidates must have a bachelor’s degree from Duke University.
  • Candidates with a Bachelor’s degree in data science, computer science, electrical and computer engineering, statistics, and/or mathematics are encouraged to apply.
  • Candidates must demonstrate experience with one or more programming languages or statistical software (e.g., Python, R, Stata, C, Java, etc.).
  • Additional preferred skills include:
    • Experience participating on a project team.
    • Ability to marshal a project to completion.
    • Demonstrated experience or coursework in quantitative disciplines, including project work in complex analyses.
    • Demonstrated experience clearly communicating complex analyses to a broad and non-technical audience.
    • Previous internship experience and/or participation in Code+ or Data+ programs.