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Greater Sudbury, Ontario, Canada
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Recent projects
Client Analysis Dashboard
We have built an internal dashboard to better understand our sales targets and statuses. This function is growing in our business and we now need to understand how we can enhance this product and where the gaps in data are to bring it to another level of analysis. The long term goal for this dashboard is to create a predictable forecast in sales and requirements. We have a code repository we can share for this work as well as internal resources for support. The following tasks will be required for this project. - data gap analysis - data visualization - data modeling
Data to map the energy sector
The main goal for the project is to create an analysis of companies involved in the energy sector using publicly available data. The students are expected to collect and organize data from various sources to create a comprehensive map of the energy sector. The outcome of the project should be a detailed analysis of the companies involved in the energy sector. This data will then be used by the data science and marketing teams. This analysis will provide valuable insights for the company, helping it make informed decisions about investments and partnerships in the energy sector.
Strategic data science software development roadmap - features and ideas
The main goal for this project is to develop a strategic data science software development roadmap for Sofvie, a company that specializes in occupational health and safety. The goal is to identify research questions of interest and set a roadmap for the development of future modules. The problem that students will be solving is to determine how the various elements that Sofvie works with can be integrated to support the data science team in their efforts to improve occupational health and safety. This will involve hypothesis testing to see if variables are related and describing ideas for future modules at the intersection of our data (what we can figure out) and helping build future development plans. This roadmap will include specific modules and features that can be implemented in the future, and will be based on research questions of interest and the integration of various elements that Sofvie works with.
Time series analysis
For this project, students will be tasked with using Python, SQL, and PySpark to analyze occupational health and safety data and make predictions. The goal of the project is to use time series analysis techniques to identify trends and patterns in the data, and to develop models that can be used to make informed predictions about future incidents and accidents. Once the data has been analyzed, students will need to use time series analysis techniques to identify trends and patterns, and to develop predictive models that can be used to forecast future incidents and accidents. These models may be implemented using machine learning algorithms or other statistical methods. Finally, students will need to present their findings and recommendations to stakeholders, possibly in the form of a report or presentation. This may involve creating visualizations or dashboards to help communicate the results of the analysis.