Data Analyst

Qualifications

• Bachelor's Degree in a related field (e.g., Mathematics, Statistics, Computer Science).
• 1-2 years of proven experience in data analysis.
• Excellent proficiency in Microsoft Excel, including advanced functions and pivot tables.
• Strong analytical and problem-solving skills.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Knowledge of database management and SQL is an advantage.
• Attention to detail and the ability to work independently.
• Effective communication skills to convey complex data findings clearly.
• Ability to work in a collaborative team environment.

Qualifications

• Bachelor's Degree in a related field (e.g., Mathematics, Statistics, Computer Science).
• 1-2 years of proven experience in data analysis.
• Excellent proficiency in Microsoft Excel, including advanced functions and pivot tables.
• Strong analytical and problem-solving skills.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Knowledge of database management and SQL is an advantage.
• Attention to detail and the ability to work independently.
• Effective communication skills to convey complex data findings clearly.
• Ability to work in a collaborative team environment.

• Data Collection: Collect and compile data from various sources, ensuring data accuracy, completeness, and timeliness.
• Data Cleaning and Preparation: Clean, preprocess, and transform raw data to make it suitable for analysis. Handle missing data and outliers effectively.
• Data Analysis: Apply statistical and analytical techniques to identify trends, patterns, correlations, and anomalies in the data.
• Data Visualization: Create clear and informative data visualizations (e.g., charts, graphs, dashboards) to communicate findings to non-technical stakeholders.
• Reporting: Generate reports and summaries of analysis results, including actionable recommendations for decision-makers.
• Hypothesis Testing: Conduct hypothesis tests to validate assumptions and hypotheses based on data.
• Data Interpretation: Translate data insights into actionable business insights that can drive strategy and decision-making.
• Data Quality Assurance: Ensure data quality, accuracy, and consistency. Implement data quality best practices.
• Collaboration: Work closely with teams across the organization, including business analysts, data scientists, and managers, to align data analysis with business goals.
• Tools and Software: Utilize data analysis tools and languages (e.g., Python, R, SQL) and data visualization tools (e.g., Tableau, Power BI).