Do you have the required Data Science skills to drive real impact at one of the most recognisable brands globally?
The AI Scientist is part of the Data Science — Growth team within the broader Data Science & Analytics organization. Leveraging deep applied experience and theoretical expertise in Artificial Intelligence, this role provides concrete deliverables to the DS&A team and the wider organization in the form of AI Governance principles, AI Service Delivery, and AI Capabilities. The AI Scientist continuously tracks advances in the field, situates them within the broader scientific context, and helps Data Science & Analytics teams make use of AI in the context of their offering to the organization (e.g., DS Services). In partnership with the cross-functional AI Governance group, they represent Global Data’s perspective, playing a leading role in delivering actionable inputs into initiatives such as AI by Design, AI Risk Classification Clusters, and Procurement and Management of AI Vendors. Additionally, the AI Scientist supports projects run by the DS&A teams by advising them and helping with the implementation of AI techniques to both existing and new Data Science & Analytics initiatives (e.g., Augmented Analytics, Market-Specific Data & AI Acceleration Programs, drive cost-efficiency in Data Harmonization initiatives, …).
RESPONSIBILITIES
Areas that play to your strengths
All the responsibilities we'll trust you with:
1. CONTRIBUTE TO THE DEVELOPMENT & DELIVERY OF AI GOVERNANCE FRAMEWORK
2. PROVIDE ACTIONABLE INPUT TO AI VENDOR STRATEGY
3. DRIVE EMBEDDING OF AI CAPABILITIES IN DS&A INITIATIVES
4. TRANSLATE AI RESEARCH INTO ORGANISATIONAL PRACTICE
5. AI THOUGHT LEADERSHIP & INTERNAL CONSULTING
6. Deep AI Expertise (proven advanced knowledge of AI across domains incl. LLMs, ML/DL, reinforcement learning, as well as the history of AI leading back to its origins).
7. Applied & Theoretical AI Knowledge (ability to translate cutting-edge AI findings into practical applications making use of the scientific method where appropriate).
8. Research Literacy (interpret, critique, and contextualize academic and industry literature).
9. AI Governance (ability to contribute to the topic of AI governance and risk management in enterprise contexts).
10. Data/Analytics Skills (applied knowledge of Python and platforms [e.g., Snowflake] to facilitate interaction with technical/data teams and deliver quick POCs/experiments).
11. Critical Thinking (ability to distinguish value from hype, particularly in the context of AI vendor procurement).
12. Communication, Storytelling, & Thought Leadership (articulate complex AI concepts to both technical and non-technical audiences in an engaging and opinionated manner).
13. Advisory & Consulting Skills (provide expert guidance in an ad-hoc fashion to diverse Data Science & Analytics teams and projects).
14. Stakeholder Management: good at building mutually beneficial connections with functional stakeholders.
15. Pragmatic Critical Thinking: intuitively consider relevant costs/benefits in all decisions and act accordingly.
16. Outcome Driven: highly motivated to add value and to demonstrate that impact to the organisation.
17. Grit: proven capability to see things through to the end even if initial feedback is discouraging.
18. Travel 0-10%
AI & Data Scientist
Red Bull
Giving wiiings to people and ideas since 1987
In the 1980s Dietrich Mateschitz developed a formula known as the Red Bull Energy Drink. This was not only the launch of a completely new product, in fact it was the birth of a totally new product category.
What drives usChasing our potential
Since the early days of Red Bull, an entrepreneurial mindset has always guided our approach to work and the environment we create: