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. Generate reports and visualizations to support planning and decision-making. Collaborate with facilities staff, planners, and IT teams to troubleshoot and improve data workflows. Participate in space audits
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Qualifications (Not Required) Python proficiency (e.g., pandas/polars; data cleaning; visualization). Experience with databases (SQL), APIs, Git/GitHub, or cloud platforms. Interest in responsible/ethical AI
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . JOB DESCRIPTION AND POSITION
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . JOB DESCRIPTION AND POSITION
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audio-visual setups, security, refreshments, and vendor-delivered meals) Manage data, files, and calendars Provide coordination and oversight for external visitors, ensuring that security guidelines and
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REQUIREMENTS The Pennsylvania State University Libraries’ Research Data Stewardship Department seeks a part-time Data Analyst position. This position will focus on collecting, analyzing, and visualizing data
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. Experience with marketing dashboard/reporting tools and data visualization. MINIMUM EDUCATION, WORK EXPERIENCE & REQUIRED CERTIFICATIONS Bachelor's Degree 8+ years of relevant experience, includes 3+ years
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: Collaborate with NCEMS Working Groups to design and implement computational methods for integrating, analyzing, and visualizing complex molecular and cellular biology data Lead data wrangling, harmonization
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . POSITION SPECIFICS A Web
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Collaborate with NCEMS Working Groups to design and apply rigorous statistical approaches for integrating, analyzing, and visualizing complex molecular and cellular biology data. Apply inferential statistics