Job Title:
Data Scientist Location:
Widnes (originally on-site then move to a hybrid arrangement) Salary:
£45,000 - £65,000 Yoh have partnered with a rapidly scaling business, pioneering and leading a data-driven technologies approach using sensor & signal detection, primarily serving clients in the Water and Oil & Gas industry. They have completed another round of funding and signed off several large projects to support their product roadmap and further develop their R&D functionality. They are looking to scale the team by hiring multiple individuals to bolster their data capabilities. Located on the outskirts of the Liverpool area, they ideally seek someone to initially join the team on-site to embed within the team and then potentially move to a hybrid basis as understanding grows. Responsibilities: Implement data and machine learning-based methods for training and validating results. Apply signal processing techniques to improve algorithm performance. Process and visualize datasets, discussing performance and accuracy. Minimum Requirements: Experience working with Python programming focused on data manipulation and analysis. Experience working with large datasets performing containerization, clustering, classification, and regression with technologies such as Docker. Experience with image processing/DAS sensors is beneficial but not necessary.
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Data Scientist Location:
Widnes (originally on-site then move to a hybrid arrangement) Salary:
£45,000 - £65,000 Yoh have partnered with a rapidly scaling business, pioneering and leading a data-driven technologies approach using sensor & signal detection, primarily serving clients in the Water and Oil & Gas industry. They have completed another round of funding and signed off several large projects to support their product roadmap and further develop their R&D functionality. They are looking to scale the team by hiring multiple individuals to bolster their data capabilities. Located on the outskirts of the Liverpool area, they ideally seek someone to initially join the team on-site to embed within the team and then potentially move to a hybrid basis as understanding grows. Responsibilities: Implement data and machine learning-based methods for training and validating results. Apply signal processing techniques to improve algorithm performance. Process and visualize datasets, discussing performance and accuracy. Minimum Requirements: Experience working with Python programming focused on data manipulation and analysis. Experience working with large datasets performing containerization, clustering, classification, and regression with technologies such as Docker. Experience with image processing/DAS sensors is beneficial but not necessary.
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