Job Description
Join the elite team at Apex Innovations, a leading top-tier tech company reshaping the data landscape. We are looking for ambitious Junior Data Analysts to join our New York headquarters. While prior experience is a plus, we strongly value potential, curiosity, and a passion for numbers. We are also open to remote candidates based in Florida and across the U.S. who are eager to launch their careers in tech.
As a Junior Data Analyst, you will play a crucial role in our decision-making process. You will work alongside senior data scientists to clean, analyze, and visualize complex datasets, turning raw numbers into actionable insights that drive business growth.
Responsibilities
- Data Collection & Cleaning: Gather and preprocess large datasets to ensure accuracy and reliability for analysis.
- Dashboard Creation: Build and maintain interactive dashboards using tools like Tableau or PowerBI to visualize key performance indicators (KPIs).
- Trend Analysis: Identify patterns and trends within data to support strategic business decisions.
- Reporting: Prepare clear, concise reports for stakeholders, translating complex data into understandable insights.
- Collaboration: Partner with marketing and product teams to understand their data needs and provide analytical support.
- Process Improvement: Assist in optimizing data workflows and suggesting improvements for data management systems.
Qualifications
- Education: Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or a related field. Recent graduates are encouraged to apply.
- Technical Skills: Basic proficiency in SQL, Excel (Pivot Tables, VLOOKUP), and experience with data visualization tools (Tableau, PowerBI) is preferred but not mandatory.
- Communication: Excellent verbal and written communication skills with the ability to explain technical concepts to non-technical audiences.
- Attention to Detail: A keen eye for detail and a strong commitment to data accuracy.
- Problem Solving: Ability to think critically and solve complex problems using data-driven approaches.