Data Analyst

Data Cleaning: Preprocessing and cleaning data to ensure it's ready for analysis.

Data Visualization: Creating charts and graphs to help interpret data.

Statistical Analysis: Conducting basic statistical tests and analysis.

Machine Learning: Assisting with the development and validation of predictive models.

Research: Gathering and summarizing research papers or related literature.

Reporting: Drafting reports and creating presentations to share findings.

Data Entry: Inputting data into databases or spreadsheets accurately.

Database Management: Helping with queries, backups, and maintaining database integrity.

Tool Development: Contributing to the creation or improvement of data analysis tools.

Automation: Automating repetitive tasks to improve workflow efficiency.

Collaboration: Working with other team members to support larger data science projects.

Educational Support: Assisting in the preparation of materials for data science education and training.

Code Review: Help review and debug code written for data analysis.

Data Ethics: Ensuring that data handling and analysis adhere to ethical guidelines.

Problem-Solving: Assisting with troubleshooting issues that arise during data analysis.