Data  Analyst (225-831)

A Data Analyst plays a crucial role in helping organizations make data-driven decisions. By collecting, processing, and analyzing data, they provide valuable insights that inform business strategies and optimize operations. They work across various departments to understand data requirements, design data collection structures, and cleanup raw data. Moreover, Data Analysts leverage statistical and programming skills to interpret complex data sets and convey findings in a manner that is accessible to non-technical stakeholders. Their work not only highlights trends and patterns but also identifies anomalies that could signal potential issues. As a Data Analyst, you will be pivotal in driving business performance and helping your company maintain a competitive edge in its industry.

Responsibilities

• Collect and cleanse data to ensure accuracy and relevance for analysis.
• Design and maintain databases and data systems from various sources.
• Use statistical tools to identify trends and patterns in datasets.
• Work closely with management to prioritize business and information needs.
• Analyze data using advanced analytical techniques and interpret results.
• Translate complex data findings into understandable business insights.
• Develop reports and presentations to illustrate analytical findings.
• Monitor data integrity and suggest improvements for data collection processes.
• Collaborate with IT teams to enhance data collection procedures.
• Create and manage dashboards for real-time data visualization.
• Ensure compliance with data privacy regulations and best practices.
• Stay updated with the latest technology and methodologies in data analysis.

Requirements

• Bachelor’s degree in Computer Science, Statistics, or a related field.
• Proficiency in data analysis tools such as Python, R, or SQL.
• Strong knowledge of data visualization software like Tableau or Power BI.
• Excellent problem-solving skills with a keen eye for detail.
• Ability to communicate complex data insights to non-technical audiences.
• Experience in data modeling, data mining, and database management.
• Strong understanding of statistical methodologies and data analytics.