Junior Data Analyst 06J26

A Junior Data Analyst plays a crucial role in helping organizations make data-driven decisions through the collection, processing, and analysis of data. This entry-level position requires a candidate with a passion for discovering the hidden insights within large datasets. A Junior Data Analyst works closely with senior analysts and stakeholders to ensure data accuracy, develop reports, and generate actionable insights that can drive business strategies. The role demands a methodological approach, attention to detail, and a proficiency in using analytical tools and software. Consequently, this role serves as an excellent opportunity for growth and skill development for those beginning their careers in data analytics.

Responsibilities

• Collect, clean, and preprocess data from various internal and external sources.
• Assist in the development and maintenance of data collection systems and data pipelines.
• Perform exploratory data analysis and assist in creating detailed reports.
• Collaborate with senior data analysts to refine data management techniques.
• Provide data-driven insights to support strategic decision-making processes.
• Assist in the preparation of presentations for stakeholders using data visualization tools.
• Maintain database integrity and security by following established protocols.
• Support the identification and resolution of data discrepancies and anomalies.
• Compare current data with historical data to track progress and identify trends.
• Continuously update knowledge of data analysis techniques and industry best practices.
• Collaborate with cross-functional teams to gather data requirements and specifications.
• Document all data processes and methodologies used in analysis and reporting.

Requirements

• Bachelor’s degree in Mathematics, Statistics, Computer Science, or related field.
• Basic understanding of statistical analysis and data cleaning techniques.
• Proficiency in Microsoft Excel and familiarity with other data analysis tools.
• Strong analytical skills and an aptitude for recognizing patterns in data.
• Effective communication skills for presenting findings to non-technical audiences.
• Demonstrated ability to manage multiple tasks and meet tight deadlines concurrently.
• Familiarity with programming languages such as Python or R is a plus.