Technical and Competitive IT (TaCIT) delivers differentiated capabilities by combining complimentary Technical, business, and IT skills together to create, deploy, and support cutting-edge IT solutions.
VP Digitalisation (PTT/D) organisation is accountable for refreshing and maturing targeted Technology Innovation Themes and related technology platforms along with the capability build through Centres of Expertise (CoE) necessary for leveraging digital technologies across RDS.
The Advanced Analytics CoE (AA COE) is a part of the VP Digitalisation (PTT/D) organisation within TaCIT and is accountable for developing innovative advanced analytics capabilities, maturing them, and transitioning them to the analytics organisations within the broader IT function. The Advanced Analytics CoE works with the innovation team and the other CoEs within the VP Digitalisation organisation (Mobility, Computation etc.) to develop innovative digital products.
Within the AA COE organisation, the Data Science team is responsible for delivering the Data Science elements of advanced analytics projects. The Data Scientists need to work closely with Data Engineering and Software Engineering teams to ensure that appropriate technical support is provided throughout the lifecycle of Advanced Analytics projects.
The Computer Vision Specialist / Data Scientist will work in our Machine Vision team within the broader AA COE Data Science team. Within the organization there is a huge amount of data collected in the form of images and videos and we have a dedicated Machine Vision team working on extracting useful information from the data to help business decisions.
As a Computer Vision Specialist, you will be responsible for using cutting-edge technology to deliver Computer Vision projects leveraging, for instance, Deep Learning frameworks for object detection and recognition. They should have a deep understanding of Computer Vision algorithms and tools.
You should be expert-level in at least one 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 (e.g. Lidar, EDGE inference) can be used to enable business use cases.
You will use your expertise to build Data Science workflows with support from Business Analysts and data SMEs/users. These solutions will be useful to business end-users, and scalable within the existing software landscape.
Responsible for development & delivery of computer vision solutions in an agile fashion to enable insights & improvements to Shell’s business data and processes.
- 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 the infrastructure
- Accountable for developing algorithms and testing algorithms with business
- Accountable for assessing new Computer Vision technologies and techniques in terms of viability for the organization.
- Accountable for supporting development of the digital strategy for computer vision
- 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. AWS, Google, Microsoft)
- Dealing with a multinational work environment and stakeholders
Skills & Requirements:
- Bachelor or Master degree in computer science, computer vision, machine learning or relevant areas
- PHD in relevant domain is strongly preferred
- Proven practical experience with relevant topics and frameworks in computer vision and machine learning
- Practical experience designing and developing real-time Computer Vision algorithms on edge devices is highly preferred
- Experience with one of the following deep learning frameworks such as TensorFlow, Keras, PyTorch, or Caffe2, etc
- Good knowledge on Linux, OpenCV and relevant Computer Vision libraries
- Close familiarity with the latest research on Computer Vision techniques, such as detection, segmentation, classification, tracking and SLAM, etc
- Good knowledge of Python or C++
- Good understanding of mathematics and algorithms is a strongly preferred
- Ability to write clean, elegant and maintainable production-level code
- Creative problem solver and team player with strong communication skills
Interested? Send us your English CV, motivation and hourly rate!