Data Collection & Cleaning:
Gather, clean, and preprocess data from multiple sources (e.g., databases, APIs, flat files) to ensure data quality and consistency for analysis.
Data Analysis & Interpretation:
Analyze large datasets to identify trends, patterns, and correlations, providing actionable insights for business stakeholders.
Reporting & Dashboards:
Create and maintain reports, dashboards, and visualizations using tools like Power BI, Tableau, or Excel to communicate findings and key metrics to stakeholders.
Predictive Modeling & Forecasting:
Build statistical models and machine learning algorithms to predict future trends, behaviors, or outcomes (e.g., customer churn, sales forecasting).
Statistical Analysis:
Use statistical methods to test hypotheses and validate findings. Perform A/B testing, regression analysis, and other statistical analyses to drive decision-making
