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Junior Data Analyst
Artisan Talent
New York, NYOn Site
Original Job Summary
About the Role
The Junior Data Analyst at Artisan Talent will support the world’s leading academic medical center with data management, reporting, and analysis.
You Will
- Coordinate and manage provider data
- Perform accurate data entry and analytics within Excel and Caspio
- Monitor and maintain databases to ensure integrity and consistency
- Run reports and extract data using basic programming languages
- Support internal teams with reporting and troubleshooting
- Track and manage tasks using tools like Monday.com and Jira
You Have
- 3+ years of data management experience
- Strong proficiency in Excel including formulas, pivot tables, and data analysis
- Experience with database management (Caspio or similar platforms)
- High level of data entry accuracy
- Knowledge of HTML, SQL, Python, Tableau
- Familiarity with CMS platforms, Monday.com or Jira
- Excellent organizational and communication skills
- Ability to work independently in a remote setting
Logistics
- Start Date: ASAP
- Duration: Ongoing with potential to convert
- Hours: 35 hours per week
- Work Arrangement: Fully remote during EST hours
- Laptop provided
- Reporting to: VP, Digital Communications
- No background check required
- Salary: $30-35 per hour
Key skills/competency
- Data Management
- Excel
- Database
- Analytics
- Data Entry
- SQL
- Python
- Tableau
- HTML
- Communication
How to Get Hired at Artisan Talent
🎯 Tips for Getting Hired
- Customize your resume: Highlight data management skills and Excel expertise.
- Emphasize remote experience: Detail work in fully remote settings.
- Research Artisan Talent: Understand the academic medical center's mission.
- Prepare for technical review: Showcase database and analytical projects.
📝 Interview Preparation Advice
Technical Preparation
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Review Excel advanced formulas and pivot tables.
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Practice basic SQL query and Python scripting.
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Familiarize with database management tools.
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Learn Caspio or similar platform basics.
Behavioral Questions
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Describe a data error resolution instance.
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Explain managing multiple deadlines remotely.
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Discuss teamwork in data projects.
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Share an experience overcoming data challenges.