Chief Data Scientist

2 weeks ago

London, United Kingdom IAG Tech Full time

Job Description

IAG.ai represents IAG’s strategic investment in data science, machine learning, artificial intelligence and generative AI. The mission is to apply these and other modern technologies to drive material benefit across all parts of the Group, including British Airways, Aer Lingus, Iberia and Avios.

Launched in London in 2023, IAG.ai aims to partner with world-renowned academic and research institutions to establish an enduring community of AI practitioners, who can deliver tangible benefits for our customers, our business, and our planet. In parallel with delivering value, we combine a product mindset with a relentless focus on continuous improvement to continually strive to find new and better ways to innovate and support the Group through the application of contemporary technology and modern ways of working.

Purpose of the role

As chief data scientist for IAG,ai, you will be pivotal in maximising the ROI of the Group’s investments in machine learning and artificial intelligence. You will work closely with the Group Head of AI and data teams to promote re-use, establish appropriate standardisation, and help direct investment in shared AI patterns and products which can be used by multiple operating companies (airlines).

You will lead a community of talented data scientists, and foster a culture of innovation, collaboration, and excellence. You will also collaborate with other senior leaders and stakeholders across the organisation, and contribute to the development and delivery of group-wide data products and solutions.

Responsibilities

  • Work with the Heads of AI to ensure viability and value are represented when considering opportunities for AI application across the Group, and support ongoing curation of the Group’s AI catalogue and backlog
  • Establish patterns and principles for the data science technology stack, ensuring scalability, reliability, and security of the data infrastructure and platforms
  • Maximise the productivity and efficiency of the data science team, by syndicating and embedding an appropriate delivery approach, and by ensuring safety, responsibility, model risk management and other similar considerations are facets of the route to live
  • Direct content for the AI Academy, supporting continuous improvement and learning, and ensuring colleagues stay abreast of recent AI developments
  • Challenge stakeholders across the organisation, increasing awareness of the “art of the possible” (including “bringing the outside in” through external sources, speakers and perspectives), to identify further opportunities to drive value through AI application
  • Contribute to the group-wide feature store and data products
  • Stay abreast of the latest trends and developments in data science, evaluating and evangelising new tools and techniques as appropriate
  • Communicate and present data science insights and recommendations to senior management and other stakeholders, using clear and compelling visualisations and narratives
  • Build and maintain strong relationships with internal and external partners, and identify and pursue new opportunities for data science collaboration and innovation.

Qualifications, Experience, Qualities

To be successful in this role you will have PhD in Data Science or related mathematical discipline(s). Demonstrable experience in data science, with a proven track record of leading delivery of tangible value (EBIT, NPS etc.)

Consulting experience and Airline industry would be preferred, however you should be an expert in a variety of data science techniques and tools, such as machine learning, deep learning, natural language processing, computer vision, data mining, data visualisation, etc.

Proficiency in Python, R, SQL, and other programming languages and frameworks for data science. Experience in working with big data technologies and platforms, such as Hadoop, Spark, Kafka, etc.

Strong leadership, communication, and interpersonal skills, with the ability to inspire and motivate a diverse and cross-functional team. Strategic and analytical thinking, with the ability to translate business problems and opportunities into data science solutions and actions.

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