Automated Writing Feedback Systems Impact Fellow

Remote - Washington, DC

Washington D.C. – Full-Time – Remote

Application closes on September 6, 2022 at 12:00pm ET.


The FAS Day One Talent Hub is seeking a fellow for a 1 year term (with potential opportunity to extend) to join the Institute for Educational Sciences (IES) at the Department of Education (ED). 

IES is searching for a data scientist who will lead a first-of-its-kind effort to fundamentally change teachers’ ability to teach and engage students in writing. This fellow will use their expertise to analyze student writing using natural language processing and using results to inform scoring and create tutoring  engines to provide students with feedback. Expertise in other education content areas is an asset. The successful candidate will also have experience organizing and executing data competitions or designing programs of research and development.


The Fellow’s duties and responsibilities while they are appointed to NCES/IES will include but

are not limited to the following:

  • Working with staff at NCES and NAEP contractors to construct data sets and to analyze writing assessment data (cognitive and non-cognitive student responses) and process data from the same assessment as well as data from other assessments and surveys conducted by NCES and IES

  • Applying a variety of analytical approaches, including machine learning, predictive analytics, natural language processing, and classic inferential statistics in the use of NCES data in Automated Item Generation (AIG), and to create AI-enabled intelligent tutoring models to provide individualized  feedback in response to students’ writing 

  • Preparing data from NAEP and other NCES and IES data sets for use by researchers, statisticians, and interested others

  • Organizing, publicizing, managing, and administering data science competitions that use NAEP data

  • Developing technical assistance resources for researchers interested in working with the

NCES/Assessment Division’s data

  • Attending conferences and meetings that will inform the work that the Fellow is doing for


  • Supporting NCES meetings through both planning and presenting

  • Applying methods such as learning engineering and natural language processing to conduct research focused on aspects of student achievement and performance issues involving single-event and longitudinal data

  • Working quickly and communicating effectively on a wide variety of topics and working cooperatively with individuals having diverse viewpoints

  • Completing other related duties as assigned


A minimum of five years post-degree experience is preferred for Fellows selected for the FAS Impact Fellowship Program and appointed at IES.

Ideal candidates will have the following experience: 

  • Experience applying machine learning and data science methods to large, complex data sets, preferably within an education context

  • Demonstrated experience using natural language processing to analyze students’ writing

  • Experience creating and using algorithmic solutions to create feedback systems and electronic tutors

  • Knowledge of learning engineering and software development practices and procedures

  • Familiarity with FERPA and student data privacy regulations

  • Exemplary follow-through and flexibility and the ability to work independently

  • Experience organizing data science competitions

  • Strong speaking, writing, and presentation skills

Candidates must meet the following criteria: 

  • Ph.D. or Ed.D. strongly preferred

  • Be a U.S. Citizen

  • Be able to clear a background investigation for suitability/clearance issues and  verification that they have not defaulted on any loan funded or guaranteed by ED.

  • The FAS fellowship program will not consider candidates who are current federal employees.


This fellowship will provide a salary that accounts for the cost of benefits for the entirety of the fellowship duration at an annual rate ranging from $160,000 per year, commensurate with experience and education. Additional information about the Fellowship can be found in our FAQ.


To apply, please submit your interest here. We strongly encourage candidates from all backgrounds to apply. Early submission will ensure your application receives full consideration.


The FAS Impact Fellowship is a selective fellowship program that supports the development and placement of emerging scientific and technical talent within high-impact roles across the federal government. From education to clean energy, immigration, wildfire resilience, national security, and fair housing, Impact Fellows are serving across a variety of federal agencies in roles that augment existing government teams as they confront some of the greatest scientific and social challenges of our time.