Key Responsibilities
Data Collection & Analysis
- Collect, clean, organize, and analyze large datasets from multiple internal and external sources
- Identify trends, patterns, correlations, and business opportunities through exploratory data analysis
- Perform statistical analysis, predictive modeling, and data interpretation to support decision-making
- Develop and maintain databases, spreadsheets, and data systems ensuring accuracy and consistency
- Apply advanced analytical techniques to solve complex business problems
Data Visualization & Reporting
- Design and develop dashboards, reports, and visualizations using Power BI and Tableau
- Create executive-level presentations and summaries translating data into actionable insights
- Build automated reporting systems for real-time business performance tracking
- Ensure visualizations are clear, intuitive, and tailored to stakeholder understanding
Business Intelligence & Insights
- Develop KPI dashboards to monitor business performance and operational efficiency
- Identify improvement opportunities and support business optimization initiatives
- Assist in forecasting, budgeting, and strategic planning through data modeling
- Monitor trends and provide proactive insights for business growth
Stakeholder Management & Collaboration
- Present findings and insights to leadership, business units, and cross-functional teams
- Translate business requirements into analytical solutions and frameworks
- Collaborate with stakeholders to define metrics, benchmarks, and performance indicators
- Facilitate data-driven discussions and provide analytical consultation
Tools, Programming & Technologies
- Use Power BI, Tableau, Excel, SQL, Python (Pandas, NumPy), and R for data analysis and reporting
- Write complex SQL queries including joins, CTEs, and window functions
- Develop Python/R scripts for data manipulation, statistical analysis, and automation
- Build advanced Excel models using pivot tables, Power Query, and advanced formulas
- Work with databases such as MySQL, PostgreSQL, and MongoDB
Data Quality & Governance
- Ensure data accuracy, consistency, and integrity through validation and quality checks
- Perform data cleaning, transformation, and standardization
- Document data sources, methodologies, and analytical processes
- Maintain data governance standards including version control and documentation
- Conduct regular audits of datasets and reports
