Data Scientist

1. Data Collection and Cleaning:

• Gather and preprocess raw data from various sources.
• Clean and organize data to ensure it's ready for analysis.

2. Data Analysis and Exploration:

• Explore data to uncover patterns and trends.
• Use statistical techniques to analyze data and draw meaningful conclusions.

• Create visualizations such as charts, graphs, and dashboards to represent data findings.
• Communicate complex data insights in a clear and understandable manner.

4. Building Predictive Models:

• Develop and train machine learning models to predict future trends or outcomes.
• Evaluate and fine-tune models for optimal performance.

5. Business Problem Solving:

• Collaborate with business stakeholders to understand their needs and challenges.
• Translate business problems into data-driven solutions.

6. Reporting and Communication:

• Present findings and insights to both technical and non-technical audiences.
• Create reports and documentation to support decision-making.