Job Description
Join Chicago Analytics Solutions as a Data Analyst and experience the flexibility of daily pay with full relocation assistance! We're seeking a detail-oriented professional to transform raw data into actionable insights for our Fortune 500 clients. Enjoy competitive daily compensation while working in Chicago's vibrant Loop district, with comprehensive support for your relocation journey. This contract position offers immediate start dates and the opportunity to work on high-impact projects across finance, healthcare, and retail sectors.
Why Apply? Daily pay eliminates payroll wait times, relocation assistance covers moving expenses, and flexible scheduling allows work-life balance. Our collaborative team environment includes mentorship from senior data scientists and access to cutting-edge analytics tools.
Responsibilities
- Analyze complex datasets using SQL, Python, and R to identify trends and business opportunities
- Create interactive dashboards and visualizations using Tableau and Power BI for executive stakeholders
- Develop statistical models to forecast market behaviors and optimize operational efficiency
- Clean, preprocess, and validate data ensuring accuracy across multiple sources
- Present findings to cross-functional teams through clear, data-driven narratives
- Collaborate with product teams to define KPIs and track performance metrics
- Document methodologies and maintain reproducible analysis pipelines
Qualifications
- Bachelor's degree in Statistics, Mathematics, Computer Science, or related field
- 3+ years of experience in data analysis or business intelligence roles
- Expert proficiency in SQL and at least one statistical programming language (Python/R)
- Advanced skills in data visualization tools (Tableau/Power BI)
- Strong understanding of statistical methods and experimental design
- Experience with ETL processes and cloud platforms (AWS/GCP/Azure)
- Excellent problem-solving skills with attention to detail
- Ability to communicate technical concepts to non-technical stakeholders