Director, Research Intelligence & Technology Transformation - ORIED

University of Tennessee

knoxville, TN

Job posting number: #7234331

Posted: April 2, 2024

Application Deadline: Open Until Filled

Job Description

Job Summary/Essential Job Functions:

The Director works at the intersection of traditional data informatics and advances in automation and artificial intelligence and develops data analytics and technology transformation strategies that advance the mission and goals of the research enterprise at the University of Tennessee, Knoxville (UT). The Director manages the Research Informatics unit within the Office of Research, Innovation, and Economic Development (ORIED), and works directly with senior UT executives to generate, maintain, analyze, and present information that informs UT’s implementation of strategic initiatives necessary to become a top 10 public research university without a medical school. Critically, the Director must develop a deep, contextualized understanding and mastery of UT’s research data environment, as the position provides university leaders with insights into the what and why behind UT’s research performance. Further, the Director serves as ORIED’s technology transformation leader, working with staff across all ORIED divisions to operationalize technology solutions that improve and augment existing capabilities for workload management and decision-making.



Duties and Responsibilities

Research Intelligence Leadership

• Serves as lead expert in research intelligence for the UT research enterprise.

• Develops a deep, contextualized understanding of how research data are defined and used, within both a national (e.g., NSF HERD) and a UT-specific context.

• Provides university executives with data-informed recommendations and analysis to support strategic goal-setting.

• Supports the development and deployment of analytical tools and methods to maximize the utility of existing datasets that characterize the UT research enterprise.

• Develops and maintains procedures for the continued improvement and efficiency of report generation processes.

• Leads the development of better business processes to enhance the ability of all university investigators to compete for external funding.

Research Intelligence Reporting and Dissemination

• Supports the dissemination of research data for use by all UT entities, including quality control of all reports produced by the unit.

• Creates and oversees the processes to prepare timely reports based on highly specific requirements, including monthly and annual research reporting; cyclical academic program reviews; and unique, often complex ad hoc data requests.

• Leads the development and use of software tools to create dashboards and reports for all university units.

Technology Transformation Leadership

• Ideate information technology solutions with ORIED staff, helping them imagine the possibilities for how to fully exploit advances in artificial intelligence, machine learning, and automation for continuous improvement of work processes.

• Develop and deploy tools to operationalize advances in information technology within and across ORIED divisions.

• Automate manual, routine tasks, notifications, and reports to improve data integrity, workflow processes, and workload management, allowing ORIED staff to focus on more impactful work, increasing their efficiency and availability to the UT research community, and closing process gaps.

Management

• Provides quality control of work deliverables, with an emphasis on data contextualization, interfacing between customers and subordinates to ensure the accuracy of reports.

• Determines standards, deadlines, and milestones for subordinate staff work assignments, including vetting requests for assistance.

• Provides thoughtful leadership and management to subordinate staff, with an emphasis on professional growth and development.

• Interfaces with customers to ensure satisfaction with team work products.

Advocacy and Engagement

• Promotes a culture within ORIED and across UT supporting data integrity.

• Identifies enterprise-level solutions to continually improve data collection, dissemination, and reporting, and provides insights into the strategic advantages of state-of-the-art research analytics tools and the value they confer to strengthen UT’s enterprise.

Required knowledge, Skills, and Abilities

• Analytical and strategic thinking skills, with meticulous attention to detail.

• Ability and demonstrated experience with collecting, analyzing, and presenting qualitative and quantitative data for informed decision-making.

• Knowledge of advanced research methods, statistical techniques, and quantitative methodology.

• Extensive working knowledge of programming languages, databases, and reporting tools, for analytics (for example, PowerBI or Tableau), data science (for example, Python or R), compute environments (for example, Azure, Amazon AWS, or Google Cloud), and automation (for example, GPT models or LLMs).

• Extensive working knowledge of programs for word processing, spreadsheets, presentations, and other general office software, especially MS Office products.

• Excellent written and verbal communication skills.

• Ability to manage multiple complex assignments in a timely manner and with a high degree of quality.

• Ability to effectively present and defend data results.

• Ability to establish and maintain positive working relationships.

Preferred knowledge, skills, and abilities

• Ability to design and develop methods to extract and process information for planning and policy formulation.

• Demonstrated ability to employ data analytics in the services of strategic planning, gap analyses, program implementation, and program evaluation.

• Ability to use automation tools and customize such tools for the use of others.

• Previous experience with Oracle and/or Huron Research Suite software.

Required level/type of experience and/or years of experience

Masters degree in Business, Computer Science, Data Science, or other relevant discipline.

5 years of relevant, progressively responsible experience.

Preferred level/type of experience and/or years of experience

Doctoral degree in Business, Computer Science, Data Science, or other relevant discipline.

8 years of relevant, progressively responsible experience. Any level of experience in a research-intensive (R1) university or national laboratory context.





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