The main goal of this data science internship with Sofvie is to analyze and explore occupational health and safety data in order to gain insights that will help improve workplace safety and reduce the likelihood of accidents or injuries. The data science interns will be expected to develop data models, perform data cleaning and analysis, and create data visualizations that will help identify patterns and trends in the data. The ultimate outcome is to use these insights to inform data-driven decisions that can enhance workplace safety and protect employee health.

To achieve the project goal, the data science interns will need to complete the following tasks:

1. Collect and clean occupational health and safety data from various sources.
2. Analyze the data using statistical methods and machine learning algorithms to identify patterns, trends, and anomalies.
3. Develop predictive models using the data to forecast potential hazards and risks in the workplace.
4. Create data visualizations to help communicate insights and findings to stakeholders.
5. Collaborate with the data science team at Sofvie to share findings and recommendations, and to integrate insights into workplace safety protocols.
6. Prepare a final report summarizing the data analysis, insights, and recommendations.

Throughout the project, the data science interns will be expected to communicate regularly with their primary supervisor at Sofvie and receive ongoing support and mentorship.