Data Analyst

City: Kissimmee FL/ Remote Onsite/ Hybrid/ Remote: Remote Duration: 12 weeks Rate Range: Up to$64/hr on W2 depending on experience (no C2C or 1099 or sub-contract) Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B Must Have: • 3–5+ years of Data Analysis experience • Strong proficiency in SQL and Excel (pivot tables, v-lookups, data modeling) • Hands-on experience with at least one data visualization tool (Tableau, Power BI, or similar) • Data aggregation and visualization project experience • Prior experience as a Data Analyst for a retailer • Understanding of product data Responsibilities: • Conduct detailed data analysis and ensure reporting accuracy across multiple jurisdictions. • Develop and maintain dashboards, reports, and visualizations using BI tools (Tableau, Power BI, etc.). • Acquire, filter, and clean large datasets from multiple sources to ensure data quality. • Identify trends, patterns, and inconsistencies in datasets to drive insights. • Partner with business stakeholders to gather requirements and deliver relevant reporting solutions. • Support business intelligence capability development to improve reporting and decision-making. • Communicate with international suppliers and internal teams to facilitate data collection and ensure compliance. • Maintain thorough documentation of data projects, processes, and methodologies. Qualifications: • Bachelor’s degree in Data Analytics, Accounting, Finance, or related field. • 3–5+ years of proven experience in data analysis, ideally in retail. • Proficiency with SQL and Excel, including advanced functions and data modeling. • Experience building visualizations and dashboards with BI tools such as Tableau or Power BI. • Strong analytical mindset with attention to detail and accuracy. • Ability to manage and interpret large datasets effectively. • Strong communication, organizational, and problem-solving skills. • Self-motivated, organized, and solution-oriented. Preferred: • Familiarity with Python or other data processing tools. • Experience with packaging materials and retail product categorization.