Data Collection and Processing:
- Collaborate with data engineers to identify and acquire relevant data from various sources, including databases, data warehouses, APIs, and external datasets.
- Clean, transform, and preprocess raw data to ensure accuracy, consistency, and compatibility for analysis.
Data Analysis and Interpretation:
- Apply statistical techniques, data mining algorithms, and machine learning models to analyze large datasets and extract meaningful insights.
- Identify patterns, trends, and correlations in the data and provide actionable recommendations to improve business performance.
- Perform ad-hoc analysis and hypothesis testing to address specific business questions and challenges.