Description and Requirements
• Lead the development and delivery of the AI Roadmap
• Partner with executive team to ensure AI and data strategy are aligned with our overall business strategy and communicate the impact of these strategies to the board and other stakeholders.
• Engage with Growth, Product, Risk, Compliance, Operations, and IT teams to build out set of clear AI opportunities, across customer experience, customer lifecycle management, product development, risk, compliance, contact center and service operations.
• Lead the existing team of Data Engineers and in addition build a small and highly qualified team of data scientists who will be embedded into teams to accelerate the development AI solutions.
• Stay up to date on the latest trends and best practices in AI and data analytics and ensure that Voutique is at the forefront of these trends.
• Oversee execution and delivery of AI projects through the team of inhouse scientists, data engineers as well as external network of researchers and partners.
• Ensure standardization of AI engineering, deployment, and support processes.
• Establish governance and oversight to ensure transparency, explain-ability, and monitoring of AI models.
• Establish governance mechanisms and processes to align within the BSP regulatory framework.
What we’re looking for:
• Experience of imaging and delivering 10x commercial and business value from AI.
• Strong communication skills, with the ability to communicate complex technical concepts into business examples.
• PhD or master’s related to Artificial Intelligence or Optimization techniques; Bachelor’s in engineering, computer science, or other relevant technical discipline is preferred.
• At least 10 years of experience in data analytics, AI, or a related field.
Skills that will help you in the role:
• Hands on experience and a track record of experimenting, building, deploying AI solutions and strong technical experience of AI enabling technology such as Data infrastructure, API’s, Cloud.
• Hand on experience of building and improving model accuracy through data sources, data quality, training and the application of AI tools and techniques.