Data Science AND Machine Learning

Overview:

Key Responsibilities:

• Use statistical techniques and machine learning methods to drive datadriven solutions.
• Collect clean and preprocess data from various sources.
• Develop predictive models and algorithms to solve complex business problems.
• Create data visualizations to communicate findings to stakeholders.
• Collaborate with crossfunctional teams to identify opportunities for leveraging company data to drive business solutions.
• Conduct adhoc analysis and present results in a clear manner.
• Utilize big data tools and technologies for data processing and analysis.
• Enhance data collection procedures to include information relevant for building analytical systems.
• Identify valuable data sources and automate collection processes.
• Build and maintain data pipelines for efficient data extraction and processing.
• Contribute to the development of best practices for data science at the organization.
• Stay updated with the latest technology trends in data science and apply them to operational processes.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Provide expert advice and recommendations on data analysis methods and techniques.

Required Qualifications:

• General improvements support for the application:
• Windows and Linux service support.
• GPU and CPU code support.
• Support for standard CUDA library build.
• Ability to handle multiple services per machine with a preference for GPU activation only when needed.

data science,machine learning,learning,models,algorithms,computer vision