Description
The data produced by the companies is sensitive and confidential information which is subject to strict and permanent surveillance by the data scientist Oliver.
He ensures that the information is consistent, that it is accessible to users and adapted to their needs. He is also responsible for optimizing the use of external data that can contribute to the development of their business.
- create learning algorithms for data exploitation
- Analyse results and designing decision support tools
- Organise the industrial production of models
What does data mean for a manufacturer ?
Data usage within an industrial company refers to the collection, processing, storage, and analysis of data within the company’s operations. This data can come from a variety of sources, including sensors, machinery, and other systems, and it is often used to improve efficiency, reduce costs, and make informed decisions.
In an industrial setting, data usage may involve the tracking and analysis of production metrics, such as output, quality, and efficiency. It may also involve the monitoring and analysis of equipment performance, maintenance schedules, and other operational data. This data can be used to identify trends, optimize processes, and improve overall efficiency.
Data usage within an industrial company may also involve the use of data analytics and machine learning techniques to identify patterns and trends in the data and make predictions about future outcomes. For example, an industrial company might use data analytics to identify patterns in production data that could be used to improve efficiency or to identify potential problems before they occur.
Overall, data usage within an industrial company is an important part of modern operations and can help to drive improvements and increase competitiveness.
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Job Description
Job Title: Data Scientist – Manufacturing
We are looking for a highly skilled and experienced data scientist to join our dynamic team in the manufacturing industry. The ideal candidate will have a strong background in statistical analysis, data mining, and machine learning, and be able to use their expertise to drive data-driven decision-making across the organization.
Key Responsibilities:
- Develop and maintain predictive models that optimize production processes and reduce waste, based on machine learning techniques
- Analyze complex data sets to identify trends and patterns, and provide insights that enable business stakeholders to make informed decisions
- Collaborate with cross-functional teams to identify areas of improvement in the manufacturing process and develop data-driven solutions
- Develop and maintain data pipelines that integrate data from multiple sources, ensuring data integrity and accuracy
- Conduct A/B testing and experimentation to continuously improve performance metrics across the manufacturing process
- Stay up-to-date with the latest trends and developments in data science and identify new opportunities for data-driven insights within the organization
Qualifications:
- Bachelor’s degree in computer science, statistics, mathematics, or a related field
- 3+ years of experience in data science or a related field
- Strong programming skills in Python or R, and experience with data visualization tools such as Tableau or PowerBI
- Experience with machine learning techniques, such as regression, classification, clustering, and neural networks
- Strong problem-solving skills and ability to work independently or in a team environment
- Experience with data governance, data quality, and data management best practices
- Knowledge of the manufacturing industry and experience working with sensor data is a plus
If you are a data scientist with a passion for using data to drive business value and optimize production processes, we would love to hear from you. Come join our team and help us continue to innovate and stay ahead in the manufacturing industry.
