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Business Data Analyst

  • 510037
  • Fort Worth, Texas, United States
  • Staff

Title: Business Data Analyst

Employee Classification: Business Data Analyst

Campus: University of North Texas - Health Science Center

Division: HSC-Div of Rsrch & Innovation

SubDivision-Department: HSC-Health Institutes & Centers

Department: HSC-Inst for Health Disparities-300220

Job Location: Fort Worth

Salary: Commensurate with experience.

FTE: 1.000000

Retirement Eligibility: TRS Eligible

About Us - Values Overview:

Welcome to the University of North Texas System. The UNT System includes the University of North Texas in Denton and Frisco, the University of North Texas at Dallas and UNT Dallas College of Law, and the University of North Texas Health Science Center at Fort Worth. We are the only university system based exclusively in the robust Dallas-Fort Worth region. We are growing with the North Texas region, employing more than 14,000 employees, educating a record 49,000+ students across our system, and awarding nearly 12,000 degrees each year.
 
We are one team comprised of individuals who are committed to excellence, curiosity and innovation. We are transforming lives and creating economic opportunity through education. We champion a people-first values-based culture where We Care about each other and those we serve. We believe that we are Better Together because we foster an inclusive environment of respect, belonging, and access for all. We demonstrate Courageous Integrity through setting exceptional standards and acting in the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our UNT System team.
 
Learn more about the UNT System and how we live our values at www.UNTSystem.edu.

Department Summary

The Institute for Health Disparities (IHD) conducts research, training and community outreach in the areas of minority health, health disparities and workforce diversity. Constituting the IHD are the Texas Center for Health Disparities, National Research Mentoring Network, Texas CEAL Consortium, Diversity Training Programs, AIM-AHEAD and the NIMHD Endowment.

Position Overview

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program has established mutually beneficial, coordinated, and trusted partnerships to enhance the participation and representation of researchers and communities currently underrepresented in the development of artificial intelligence and machine learning (AI/ML) models and to improve the capabilities of this emerging technology, beginning with electronic health records (EHR) and extending to other diverse data to address health disparities and inequities.

Minimum Qualifications

  • Bachelor's degree and one year of related experience; or any equivalent combination of education and experience.

Knowledge, Skills and Abilities

  • Ability to analyze data, including numerical detail, identify patterns or trends, and draw valid conclusions.
  • Ability to present various data in clear concise forms to a variety of audiences.
  • Basic working knowledge of economic and accounting principles and practices, legal statutes, and analysis and reporting of financial data.

Preferred Qualifications

  • Master’s degree in Computer Science, Information Systems, Data Science, or a related field.
  • Five (5) years of experience relevant experience in AI/ML, data harmonization, management, and quality assurance.
  • Understanding of data harmonization techniques, best practices, and knowledge of data integration tools and platforms.
  • Excellent analytical, problem-solving, and organizational skills
  • Strong communication and interpersonal skills with the ability to collaborate across teams
  • Skill in developing and maintaining good working relationships

Required License/Registration/Certifications

  • N/A

Job Duties:

  • Develop and implement data harmonization strategies to ensure data consistency and quality 
  • Create and maintain data tracking and mapping systems 
  • Develop and implement data access policies and processes to ensure efficient access to data 
  • Conduct regular audits and assessments of data, systems, and processes and address potential issues and discrepancies to enhance data quality 
  • Work closely with program personnel and stakeholders to understand data needs and requirements, provide training, and resolve data-related questions and issues. 
  • Develop and implement helpdesk procedures, protocols and training 
  • Oversee and coordinate helpdesk support for mentors and trainees by overseeing question/issue resolution, providing prompt assistance, and ensuring a seamless support experience 
  • Track and analyze helpdesk performance metrics to identify trends, areas for improvement, and training needs 

Work Schedule:

Monday - Friday; 8:00 a.m. - 5:00 p.m.

Driving University Vehicle:

No

Security Sensitive:

This is a Security Sensitive Position.

Special Instructions:

N/A

Benefits:

For information regarding our Benefits, click here.

EEO Statement:

The University of North Texas System is firmly committed to equal opportunity and does not permit -- and takes actions to prevent -- discrimination, harassment (including sexual violence) and retaliation on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, genetic information, or veteran status in its application and admission processes, educational programs and activities, facilities and employment practices. The University of North Texas System immediately investigates complaints of discrimination and takes remedial action when appropriate. The University of North Texas System also takes actions to prevent retaliation against individuals who oppose any form of harassment or discriminatory practice, file a charge or report, or testify, assist or participate in an investigative proceeding or hearing.

 

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