Manager Machine Learning

Website Shell

The Machine Learning Manager is responsible for managing the central pool of machine learning and machine vision experts within Digitalisation. The Machine Learning Manager will work closely with the Digital Product Managers and Data Science Leadership Team to ensure that appropriate machine learning support is provided throughout the lifecycle of projects.

The Machine Learning Manager is accountable for setting the strategy for the machine learning discipline within the Data Science CoE (including focusing on key emergent areas of application such as machine vision, natural language processing, deep learning and artificial intelligence). They will develop the curriculum for machine learning professionals and set standards within Shell (including tool and framework selection) and work with a broader network of stakeholders to get these standards adopted. The Machine Learning Manager will also lead the development of differentiated products developed by the team with associated go-to-market strategies (such as Machine Vision for Retail).

• Develop Machine Learning as a discipline within Digitalisation.
• Coordinate the development of standards and best practices around machine learning within Shell, considering the emergence of new technologies.
• Assure the quality of the delivery of machine learning within projects.
• Assure machine learning input into digitalisation projects is taking place.
• Work closely with IT teams to ensure continued development of the over-arching data platform and architecture.
• Oversees the supply & demand balance for the central machine learning pool (including managing relationships with 3rd party suppliers)
• Responsible for development of overall strategy for machine learning within Shell (including development of key areas of expertise such as Natural Language Processing, Deep Learning and Machine Vision)
• Accountable for the overall machine learning delivery as part of application development
• Coordinates the work of the central machine learning pool, accountable for coordinating the broader data science skill pool.
• Sets machine learning standards and approves methods for deployment (including tools and techniques)
• Provides assurance and oversight around machine learning delivery, manages the peer review process.
• Owns the training program for new data engineers/graduates within Shell
• Coordinates the machine learning stream of the analytics network to ensure connectivity to other parts of Shell
• Coordinates the requirement definition for platform development
• Stakeholder Relationship Management – Acting as a key facilitator within a global organization and externally, working across business and IT stakeholders.
• Works in a Lean development environment which requires the individual to be self-driven, take decisions independently and be flexible to cater to demand.
• Takes end-to-end accountability for strategically differentiated products being developed by Machine Learning team (for example Machine Vision).

• Interfaces with Senior leaders in both business and IT
• Commercial Awareness
• People Management
• Manages the interface with key organizational partners (FO Data Analytics) as well as key academic partners (MIT, Imperial, Cambridge, Glasgow, Lancaster)
• Maintains strong connection to CTO (technology) and Group Architecture (I&D skill pool) to ensure effective technology standards and skill pool management.
• Continuously explores the market to obtain new insights and spot opportunities for Shell from emerging technologies

Special Challenges
• Building constructive and trusting relationships with a broad array of creative and energetic personalities
• Ability to reduce complex ideas to simple, understandable language
• Tenacity to drive significant wins and outcomes
• Envision and rapidly prototype IT innovation ideas into deployable solutions
• An entrepreneurial mindset and drive
• A passionate drive to push innovation forward
• Deep love of new digital technology and the potential of data driven approaches to drive business change
• Background and desire to envision a product (such as Predictive Asset Maintenance) and drive the delivery to conclusion

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