Data Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Analyst in Minneapolis, MN (Hybrid) for a long-term contract. Key skills include data analysis, Tableau, and data quality. Experience with records management systems and tools like Excel and Cognos Analytics is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 5, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Minneapolis, MN
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🧠 - Skills detailed
#Data Quality #Tableau #Data Analysis
Role description
Title Data Analyst Location Minneapolis, MN (Hybrid) Duration Long Term Job Type C2C,W2 Job Description
Potential Assignments are:
• Complete training in the department's role, processes, and data entry practices, and complete onboarding in multiple records management systems.
• Identify data quality/data entry issues in multiple records management systems, using the systems themselves as well as other tools such as Excel, Cognos Analytics, and Tableau.
• Analyze case files and utilize case information (documents, notes, etc.) to correct data entry errors, documenting actions taken and changes made.
• Note any data entry trends and make recommendations for prevention of future data entry errors.
• Analyze existing data quality reports and make recommendation for improvement and/or new reports, assisting in this process if time allows.
Title Data Analyst Location Minneapolis, MN (Hybrid) Duration Long Term Job Type C2C,W2 Job Description
Potential Assignments are:
• Complete training in the department's role, processes, and data entry practices, and complete onboarding in multiple records management systems.
• Identify data quality/data entry issues in multiple records management systems, using the systems themselves as well as other tools such as Excel, Cognos Analytics, and Tableau.
• Analyze case files and utilize case information (documents, notes, etc.) to correct data entry errors, documenting actions taken and changes made.
• Note any data entry trends and make recommendations for prevention of future data entry errors.
• Analyze existing data quality reports and make recommendation for improvement and/or new reports, assisting in this process if time allows.
