Data Analyst
1 week ago
A data analyst is responsible for collecting, analyzing, and interpreting large sets of data to extract meaningful insights that drive informed business decisions. They utilize various tools and techniques to process and visualize data, identify trends, and present findings to stakeholders.
Office Location:1614 The Meridian, Golam Dr, Cebu City, 6000 Cebu
Work Arrangement:Hybrid Setup
Key Accountabilities- Gather and organize data from different sources, ensuring its accuracy and completeness. Clean and preprocess data to remove errors, inconsistencies, or missing values.
- Apply statistical techniques, data mining, and data modeling methods to analyze complex datasets. Identify patterns, trends, and correlations to uncover insights and provide actionable recommendations.
- Create clear and visually appealing data visualizations, such as charts, graphs, and dashboards, to effectively communicate findings and insights to non-technical stakeholders.
- Prepare comprehensive reports summarizing analysis results and key findings. Present data-driven insights in a clear and concise manner that is understandable to stakeholders at various levels of the organization.
- Conduct quality checks on data to ensure accuracy, consistency, and reliability. Perform data validation and verification processes to maintain data integrity.
- Collaborate with cross-functional teams, including business stakeholders and data engineers, to define business objectives, understand data requirements, and provide analytical support.
- Identify and analyze trends and patterns in historical data to develop forecasts, predictions, or projections that can guide future business strategies and decision-making.
- Utilize data analysis tools and technologies such as SQL, Excel, Python, R, Tableau, or Power BI to manipulate and analyze data effectively. Stay updated with the latest tools and techniques in data analysis.
- Ensure compliance with data privacy regulations and maintain confidentiality and ethical standards when working with sensitive data.
- Bachelor's Degree in Accounting or Bookkeeping, Business Administration, Computer Science, Information Technology or any related field.
- Strong analytical skills with the ability to analyze complex datasets, identify trends, and draw meaningful insights.
- Familiarity with statistical concepts and techniques, such as hypothesis testing, regression analysis, and data modeling.
- Proficiency in data visualization tools and techniques to present data in a clear and visually appealing manner.
- Proficiency in data analysis tools and programming languages such as SQL, Excel, Python, R, or statistical packages.
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