Institutional Research Data & AI Solutions Sr Analyst

Marshall UniversityHuntington, WV
Onsite

About The Position

Marshall University is seeking an Institutional Research Data & AI Solutions Sr Analyst to join the Office of Institutional Research and Planning. Reporting through Institutional Research and Planning, this position combines traditional institutional research, data analysis, and decision support with the design and development of artificial intelligence solutions that improve access to information, and institutional decision-making to support university operations. The successful candidate will analyze institutional data, support federal, state, and university reporting requirements, and conduct studies related to enrollment, retention, student success, academic programs, personnel, and institutional effectiveness. The position will also develop responsible AI-enabled applications, agents, automations, and analytical tools that help university employees locate information, interpret and analyze data and make informed decisions. Working collaboratively with Institutional Research and Planning, Information Technology, academic and administrative units, and university data stewards, the position will translate institutional data into practical analytical and AI solutions. The employee will help ensure that AI solutions are accurate, secure, appropriately governed, technically sustainable, and aligned with university policies, technology standards, data standards, and strategic priorities.

Requirements

  • Bachelor's degree in a relevant field (e.g., Institutional Research, Data Science, Computer Science, Statistics, Information Systems, Public Policy, or a related quantitative field).
  • Minimum of 5 years of experience in institutional research, data analysis, business intelligence, or a related field within higher education.
  • Proficiency in SQL for querying relational databases.
  • Experience with programming languages such as Python for data analysis, statistical modeling, and automation.
  • Experience with data visualization tools and techniques.
  • Understanding of statistical and analytical methods.
  • Familiarity with higher education data, reporting requirements (e.g., IPEDS), and common institutional research topics (enrollment, retention, student success).
  • Knowledge of data governance principles and best practices.
  • Excellent analytical, problem-solving, and critical thinking skills.
  • Strong communication and interpersonal skills, with the ability to explain complex data and technical concepts to diverse audiences.
  • Ability to work independently and collaboratively in a team environment.
  • Experience with AI concepts, machine learning, or related technologies is a plus.

Nice To Haves

  • Master's degree or Ph.D. in a relevant field.
  • Experience with specific AI technologies such as natural language processing (NLP), retrieval-augmented generation (RAG), or machine learning frameworks.
  • Experience with enterprise resource planning (ERP) systems or student information systems (SIS).
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and related AI/ML services.
  • Experience with business intelligence platforms (e.g., Tableau, Power BI, Qlik).
  • Experience in developing and deploying AI-enabled applications or agents.
  • Knowledge of cybersecurity principles related to data and AI solutions.
  • Experience with data warehousing and ETL processes.

Responsibilities

  • Collect, analyze, interpret, and communicate institutional data to support university planning, policy development, operational improvement, and strategic decision-making.
  • Conduct analyses related to enrollment, retention, persistence, graduation, student success, academic programs, workforce trends, financial planning, and institutional performance.
  • Prepare reports, presentations, visualizations, and written summaries that translate complex findings into clear and actionable information.
  • Respond to ad hoc data and research requests from university administrators, academic units, committees, and other institutional stakeholders.
  • Assist with institutional studies, benchmarking projects, surveys, program evaluations, and assessment activities.
  • Apply appropriate statistical, analytical, and research methods to evaluate institutional questions and measure outcomes.
  • Design, develop, test, and maintain AI-enabled solutions including agents, assistants, and workflow solutions that address institutional research, data, analytical, and administrative needs.
  • Lead development when the principal purpose of a solution is institutional data analysis, data interpretation, reporting, predictive analytics, or data-informed decision support.
  • Collaborate with Information Technology on AI and automation initiatives that require enterprise applications, systems integration, infrastructure, identity management, cybersecurity, or operational workflow development.
  • Provide institutional data knowledge, analytical logic, data definitions, and governance expertise to solutions led by Information Technology or other university units.
  • Create retrieval-augmented generation solutions that allow authorized users to obtain answers from trusted university documents, policies, data definitions, analytical resources, and institutional information, including the university’s data warehouse or other sources used in AI solutions.
  • Develop AI-supported workflows for information retrieval, document analysis, data interpretation, classification, summarization, routing, and other appropriate university uses.
  • Contribute institutional data expertise to enterprise applications, AI tools, and automations led by Information Technology when those solutions require university data, data definitions, analytical logic, or reporting capabilities.
  • Integrate AI solutions with approved university systems, data platforms, reporting environments, and knowledge repositories in coordination with Information Technology.
  • Monitor AI solutions for accuracy, reliability, usability, security, and continued alignment with institutional and technical requirements.
  • Maintain technical documentation, user instructions, testing records, ownership information, change logs, and support procedures for developed solutions.
  • Query, transform, validate, and analyze data from enterprise systems and relational databases using SQL and other analytical tools.
  • Use Python or comparable programming languages to support data preparation, statistical analysis, predictive modeling, automation, and AI application development.
  • Develop automated processes that improve the efficiency, consistency, and reproducibility of institutional reporting and analysis.
  • Work with structured and unstructured data from multiple institutional sources.
  • Collaborate with business intelligence and data professionals to use approved data models, semantic layers, data warehouses, and institutional reporting resources.
  • Assist with the development and validation of predictive, forecasting, or classification models related to enrollment, retention, student outcomes, and institutional operations.
  • Support the collection, validation, and submission of information required for federal, state, accreditation, and institutional reporting such as IPEDS, state higher education reporting, institutional data publications, and external surveys.
  • Apply established definitions, reporting standards, and quality-assurance procedures to ensure the accuracy and consistency of reported information.
  • Work collaboratively with the Institutional Research and Planning team to coordinate and complete institutional research projects.
  • Meet with university stakeholders to identify research questions, operational challenges, information needs, and potential AI use cases.
  • Translate business and institutional requirements into clear analytical or technical solution designs.
  • Provide demonstrations, training, documentation, and support to university employees using developed tools.
  • Promote data literacy, responsible AI use, and evidence-based decision-making across the institution.
  • Collaborate effectively with technical and nontechnical employees in academic and administrative areas.
  • Remain current with developments in institutional research, higher education analytics, artificial intelligence, data governance, and emerging technology.
  • Perform other duties as assigned.

Benefits

  • Reporting through Institutional Research and Planning
  • Opportunity to work with cutting-edge AI solutions
  • Collaborative work environment with IT, academic, and administrative units
  • Contribute to university-wide decision-making and strategic priorities
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