Product Owner in Maching Learning field

As we migrate from onpremise servers to Domino Datalab we are looking for someone with experience in navigating constraining environments and identifying solutions with available building blocks. The challenges of the platform are combining data availability security and traceability to build the Data Science platform of tomorrow.

As a Product Owner you must take into account the requirements of your stakeholders your clients (both data scientists and AI consumers) as well as current and upcoming regulations to deliver a working AI platform for both model design and industrialization.

Domino Datalab allows our data scientist to work mostly in a selfservice manner nevertheless we must propose an industrialization path for their outputs with an integration into the banking ecosystem and its constraints (integrity availability throughput ...)

Another key challenge is to make data available to data scientists in a secure and compliant way.
Access should be simple forthcoming and compliant while enabling both data exploration and usecase industrialization scenarios.

As a Product Owner you build the roadmap for the coming year making sure that the Development Team understands both the product and its target vision. With the Development Teams help you make sure that work is prioritized in consistent Sprints.

Design phase and project methodology:

• build the products big picture including its roadmap and translate this picture towards the development team
• clarify the need and draft the products key functional specifications according to the agile methodology
• iteration planning and priorities definition to ensure the proper content delivery
• defines the priorities and monitors the Product Backlog thus he continuously prioritizes the key business needs
• make sure that the different stakeholders become and stay aligned on the product to be delivered

Project followup and support:

• initiate a priority management approach ensure the product consistency and quality
• actively participate into Scrum ceremonies (agile retrospectives demo test labs)
• is the decision maker or has the authority to arbitrate on delivered functionalities
• conduct Sprints Backlog live adjustments and followup

Requirements:

• 5 years working with AI models and their deployment
  
• Fluent English
• Good command in at least one of local languages (French Dutch)

An analyst involved in Agile projects must have the Agile mindset which implies:

• a positive attitude and pragmatism
• thirst for knowledge: Agile is about learning and adapting. Knowledge sharing is key to success.
• The goal of team success: Agile is about the success of the team no individual success or heroic behavior. It is more important for the team to succeed than for the individual to have completed his/her tasks.
• There is no failure only feedback: Agile is about taking everything as lessons adjusting actions based on the feedback resulting in continuous improvement.

Beyond the roles: Agile teams are crossfunctional. All required disciplines are represented in the team (analysis development testing ). However although team members have a primary role representing a discipline they are expected to take on other roles and contribute to other disciplines whenever it helps towards reaching the sprint goal.

Telework: 50% onsite in Brussels & 50% homeworking