Hybrid Research Data Analyst - Chambers College of Business and Economics

Job Description - (Hybrid) Research Data Analyst - Chambers College of Business and Economics (28632)

(Hybrid) Research Data Analyst - Chambers College of Business and Economics 28632

The John Chambers College of Business and Economics at West Virginia University is currently accepting applications for a (Hybrid) Research Data Analyst.

Data Driven WV (DDWV) at the John Chambers College of Business and Economics is seeking a Research Data Analyst to support advanced analytics for faculty research, sponsored projects, and service initiatives. This role will focus on applying data analysis techniques to drive strategic decision-making and outcomes for various projects, particularly in the areas of research and service to West Virginia and the surrounding region.

The Research Data Analyst will work closely with faculty and research teams to ensure effective use of data and analytics throughout the project lifecycle.

We strongly believe in work-life balance and keeping time for things we love outside our work. WVU offers generous benefits, including:

• 18 sick days per year(for when you’re ill, for when you need time to care for sick family, for your own, or your family’s, regularly scheduled medical appointments. Who is family for the purpose of this leave? A lot of people in your life including immediate relatives and in-laws as well as others considered to be members of your household living under the same roof)
• 401(a) retirement savings with 6% employee contribution match, eligibility to continue health insurance, and other retiree perks. Looking for more retirement benefits information ? Check out retirement health insurance benefits, retirement income, and FAQ’s.
• Wellness programs

• Advanced Data Analysis: Perform complex data analysis, including statistical modeling, data wrangling, and data visualization, to support faculty research, grant-funded projects, and service initiatives.
• Research Support: Collaborate with research teams to design and implement data collection strategies, analyze research data, and present actionable insights that support academic and strategic goals.
• Data Visualization & Reporting: Create interactive data visualizations and reports using tools such as R Shiny, Tableau, or Power BI to present results to stakeholders and guide decision-making processes.
• Data Wrangling & Integration: Work with large datasets, ensuring data integrity and preparing datasets for advanced analytics or machine learning applications.
• Strategic Project Management: Support faculty and stakeholders in defining project goals, managing project timelines, and ensuring the effective integration of data into strategic decisions.
• Client Engagement: Communicate findings and insights clearly through presentations and reports tailored to different stakeholders, including researchers, faculty, and external partners.
• Data Systems Management: Manage and maintain databases, ensure efficient data storage, and work with database management systems to ensure data availability and integrity.
• Collaboration & Relationship Building: Build and maintain relationships with faculty, research partners, and external sponsors to foster collaboration and support the center's research initiatives.
• Grant & Proposal Support: Assist in writing data-related components for grant proposals, providing analytical support to secure research funding.

• Bachelor's degree in data analytics, engineering, computer science, or a related field.
• A minimum of one (1) year of experience in the following:
  • Experience in advanced data analytics, including statistical modeling, machine learning, and data visualization.
  • Demonstrated experience with data analysis tools and programming languages such as R, Python, or similar.
• Any equivalent combination of related education and/or experience will be considered.
• All qualifications must be met by the time of employment.

• Technical
  
  Skills:
  • Proficiency in statistical programming (e.g., R, Python).
  • Experience with data visualization tools (e.g., R Shiny, Tableau, Power BI).
  • Strong knowledge of database management and querying (e.g., SQL, No
    
    S…