Key Responsibilities:

1. Data Collection: Gathering raw data from various sources, such as databases, spreadsheets, APIs, or even web scraping.

2. Data Cleaning: Ensuring data is accurate, consistent, and complete by handling missing values, correcting errors, and normalizing formats.

3. Data Analysis: Using statistical techniques and software tools (like Excel, SQL, Python, R) to analyze and interpret data. This includes identifying trends, patterns, correlations, and anomalies.

4. Reporting & Visualization: Creating reports and visualizations (using tools like Tableau, Power BI, or matplotlib) to present findings in an understandable format for decision-makers.

5. Data Modeling: Building predictive models or analyzing relationships between variables to forecast trends or behaviors, often using statistical or machine learning techniques.

6. Collaboration: Working with other departments (marketing, sales, finance, etc.) to understand their data needs and provide actionable insights that influence business strategies.

7. Performance Metrics: Developing key performance indicators (KPIs) to track the success of business strategies and processes.