Job Description
We are currently seeking a highly analytical and detail-oriented Data Analyst to join our dynamic team in Atlanta, GA. This is a fantastic opportunity for professionals looking for immediate work with the benefit of daily pay.
In this role, you will partner with cross-functional teams to drive business decisions through data-driven insights. You will be responsible for collecting, processing, and performing statistical analyses on large datasets to uncover trends, opportunities, and operational efficiencies. Our clients value our ability to provide top-tier talent that hits the ground running.
Why Apply?
- Daily Pay Option: Get paid the very same day you work.
- Competitive Pay: Hourly rate between $45 and $65 depending on experience.
- Immediate Start: Flexible start dates available.
- Premium Benefits: Access to health, dental, and vision insurance.
Responsibilities
- Collect, clean, and validate datasets to ensure high-quality input for analysis.
- Design and develop complex SQL queries to extract and manipulate data from various sources.
- Create interactive dashboards and visualizations using tools like Tableau, Power BI, or Looker.
- Perform statistical analysis to identify trends, correlations, and outliers in business data.
- Present findings and actionable insights to stakeholders through clear reports and presentations.
- Collaborate with management to define business questions and determine data requirements.
- Monitor data quality and integrity across reporting systems.
Qualifications
- Bachelor’s degree in Finance, Mathematics, Statistics, Computer Science, or a related field.
- 2+ years of professional experience as a Data Analyst or in a similar role.
- Strong proficiency in SQL (Querying, Joins, Stored Procedures).
- Advanced Excel skills (Pivot Tables, VLOOKUP, Macros).
- Experience with data visualization tools (Tableau, Power BI, or similar).
- Experience with programming languages such as Python or R is a plus.
- Excellent problem-solving skills and the ability to communicate complex data to non-technical audiences.