Head - Artificial Intelligence/Machine Learning - Internet/Online

The Business

Role:

Primary purpose of this role is to shape the AI/ big data capabilities within the, so that they can be used to extract value from the data we hold about our customers using advanced machine learning techniques

What the Business Does:

The role is in Digital Engineering Services AI & Machine learning Centre of Excellence

Your Responsibilities:

As AI architect your key responsibilities will be:

- Responsible for the definition and communication of the application architecture (current, resultant and target states) for AI & ML, ensuring application architecture links to the overall organization strategy and satisfies the business, customer and architecture outcomes

- Defines, creates and manages multi-year roadmaps for applications.

- Collaborates with data science teams to gather requirements for AI and ML use cases

- Produces technical specifications for BigData and other relevant platform teams to delivery against (e.g. Solution Design Documents)

- Hosts/chairs forums for Data Science collaboration

- Keeps up to date with market developments and identify tooling or techniques to be on-boarded to the organization

- Supports architecture team development and training through sharing knowledge and skills

- Proactive identification and effective management and/or escalation of conduct risk to deliver key customer outcomes (mandatory wording)

The skills you will need:

- In-depth knowledge and experience of AI/ BigData products and frameworks (e.g. IBM Watson Chatbot, Deep learning platforms- Tensor flow, H2O, - Numpy packages for Bayesian probabilistic graphs, Reinforcement learning, Cloudera Hadoop), preferably, certified by Cloudera or similar

- Person will have hands on experience of architecting and developing AI/Chatbot and or other AI solutions, Design technical roadmap of chat-bot strategy

- Liaise with the cloud development manager to create the technical design

- Consulted on A.I strategy and machine learning capabilities at enterprise level.

- Experience of AI & ML leading a data scientist team in a similar organization

- A computing academic degree and preferably additional academic qualifications in mathematics or statistics or data science

- Experience as a technical or business architect in a similar organization with knowledge of architecture frameworks (e.g. TOGAF, Archimate)

- Knowledge and experience of Data Integration and warehousing frameworks (e.g. Kimball, Inmon)

- Knowledge and experience of Cloud based AI & - ML as a service- (e.g. AWS Sagemaker, Azure ML)

- Experience of working with technology vendors and products within the Market