Entry Level Data Analyst
Matricstek Inc.
Florida, United StatesFresher6h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 1 year · Bachelor's degree
- Must know
- Data analysisSQLExcelPower BITableauData visualization
- Nice to have
- PythonPandasNumPy
- Work
- On-site in Florida
- Pay
- Not stated by the employer.
- Skill demand
- Data analysis94%Excel72%SQL64%Power BI61%of 72 similar entry-level jobs posted in the US this week
- Listed
- Oct 30, 2026 · still open
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About the Role
We are looking for a detail-oriented and analytical Entry-Level Data Analyst to join our team. This is an excellent opportunity for fresh graduates to develop their analytical skills and gain hands-on experience working with real-world datasets and business problems.
Key Responsibilities
- Collect, clean, validate, and organize data from multiple sources.
- Analyze datasets to identify trends, patterns, and meaningful business insights.
- Write basic SQL queries to retrieve, filter, and manipulate data.
- Use Microsoft Excel to perform data analysis, create reports, and manage datasets.
- Create dashboards and visual reports using Power BI or Tableau.
- Assist in preparing daily, weekly, and monthly reports for business teams.
- Identify data inconsistencies and support data quality improvement initiatives.
- Collaborate with cross-functional teams to understand business requirements.
- Document analysis processes, findings, and reporting procedures.
Requirements & Tech Stack
- Basic knowledge of SQL and relational databases.
- Good working knowledge of Microsoft Excel, including formulas, sorting, filtering, and pivot tables.
- Basic understanding of data visualization tools such as Power BI or Tableau.
- Familiarity with Python and libraries such as Pandas and NumPy is an advantage.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Statistics, Mathematics, Business Analytics, or a related field.
- Strong analytical, problem-solving, and logical-thinking abilities.
- Good communication skills and attention to detail.
- Willingness to learn new technologies and work with large datasets.
- Academic projects or internships involving data analysis.
- Basic understanding of data cleaning, data transformation, and statistical concepts.
- Familiarity with reporting, dashboards, and key performance indicators (KPIs).