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Within our clients' organisation there is a huge amount of data collected in the form of images and videos and there is a dedicated Machine Vision team working on extracting useful information from the data to help business decisions. As a Computer Vision Data Scientist, you will be responsible for using cutting-edge technology to deliver Computer Vision based solutions leveraging, for instance, Deep Learning frameworks for object detection and recognition. You should have a deep understanding of Computer Vision algorithms and tools. You should be excellent in Python (or an equivalent programming language) and know how to deploy it into productive, business-facing software applications. You should have a good understanding of state-of-the-art Computer Vision technologies and be willing to explore how new technologies and approaches can be used to enable business use cases

Job Purpose

Responsible for development & delivery of computer vision solutions in an agile fashion to enable insights & improvements to business data and processes. 

Accountabilities

• Accountable for working with business to prepare requirements and technical feasibility for computer vision projects, based on data and hardware requirements.
• Accountable for designing & testing computer vision algorithms (with the support of data engineers) and deploying these algorithms within infrastructure.
• Accountable for developing algorithms and testing algorithms with business.
• Accountable for assessing new Computer Vision technologies and techniques in terms of viability for our client.
• Accountable for supporting development of the digital strategy for computer vision.

Special Challenges:

• Building constructive and trusting relationships with mostly remote business stakeholders.
• Dealing with challenges in data acquisition from other parts of the business.
• Working with different vendors to develop understanding of the state-of-the-art computer vision techniques and technologies (e.g. Azure, AWS, Google, etc.)
• Dealing with a multinational work environment and stakeholders.

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