Qualifications: Bachelor s Degree in Data Science, Statistics, Mathematics, Computer Science, Economics.
Fresh graduates or individuals with minimal professional experience are encouraged to apply.
This role offers a valuable opportunity to gain hands-on experience in data analysis, work with real-world datasets, and contribute to projects that impact decision-making. Join us and be part of a team that values curiosity, innovation, and collaboration in the realm of data analysis.
Required Technical Skills:
Proficiency in data analysis tools such as Excel, Python, R, or SQL.
Basic understanding of data visualization tools like Tableau, Power BI, or similar.
Desired Skills:
Familiarity with statistical analysis concepts and techniques.
Strong attention to detail and ability to work with complex datasets.
Good problem-solving skills and the ability to draw meaningful insights from data.
Effective communication skills to present findings and insights.
Eagerness to collaborate with cross-functional teams and contribute to data discussions.
Must-Have:
A genuine interest in data analysis and a willingness to learn and adapt.
Basic understanding of data collection, cleaning, and transformation.
Eagerness to understand business objectives and contribute to data-driven decision-making.
Strong organizational skills and the ability to manage and prioritize tasks.
Ability to work collaboratively and contribute to a positive team environment.
Openness to receiving guidance and learning from senior team members.
Willingness to adapt to new tools and techniques in the field of data analysis.
Responsibilities :
Collaborate with senior data analysts to assist in data collection, cleaning, and preparation.
Use data analysis tools to explore and analyze datasets to uncover trends and insights.
Collaborate with cross-functional teams to understand data requirements and objectives.
Assist in creating data visualizations and reports to communicate findings effectively.
Learn and apply basic statistical techniques to draw meaningful conclusions from data.
Contribute to the documentation of data analysis processes and findings.
Engage in continuous learning to stay updated with data analysis trends.
Adapt to changing project requirements and contribute to team goals.