About the position
Job Description
Prioritise and continuously maintain the product backlog to align with customer requirements and organisational goals.
Define clear acceptance criteria and the definition of done for backlog items.
Allocate budget and resources across feature teams and make trade-off decisions based on capacity and customer benefit.
Collaborate with stakeholders to determine strategic direction and ensure delivery of maximum customer value.
Manage activities necessary for development, operation and maintenance of software/IT solutions.
Ensure models and data pipelines are transferred and integrated into the appropriate infrastructure.
Drive continuous evaluation of market technology developments and update solution approaches accordingly.
Develop and maintain reusable technological solution blocks and integrate them into existing data infrastructures.
Apply test-driven development and CI/CD practices to ensure quality and rapid delivery.
Support internal change processes and foster improvements in team dynamics and agile working models.
Act as primary liaison between internal teams and external IT providers to ensure successful implementation and problem resolution.
Minimum Requirements:
SKILLS REQUIREMENTS:
Qualifications/Experience:
Extensive experience in product management or sub-product ownership for software or IT solutions, with responsibility for a clearly defined product scope.
Strong background in data science, AI engineering or data engineering including practical experience with ML model development and deployment.
Demonstrable experience working in agile teams (Scrum) and coordinating feature teams to deliver customer value
Essential Skills Requirements:
Deep experience in product backlog management, including prioritisation and defining acceptance criteria and definition of done.
Proven ability to distribute budget and resources across feature teams and make trade-off decisions.
Strong stakeholder management and communication skills to bridge product vision and feature teams.
In-depth knowledge of data science and AI solution design, including data pipelines and machine learning model lifecycle.
Familiarity with agile ways of working (e.g., Scrum) and improving agile practices across teams.
Technical understanding of data analytics, data visualisation tools and programming used to prepare and extract knowledge from data.
Ability to evaluate and recommend evolving technologies and build reusable solution blocks (building blocks).
Experience coordinating cross-functional teams for development, operation and maintenance of software/IT solutions (DevOps mindset).
Strong decision-making and problem-resolution skills when taking end-to-end responsibility for functions or products.
Advantageous Skills Requirements:
Hands-on experience implementing data and machine learning models in production environments.
Background in designing AI solution architectures that consider scalability, reliability and data governance.
Familiarity with test-driven development and continuous integration/deployment practices.
Experience developing reusable technological solution blocks and integrating them into existing data infrastructures.
Knowledge of assessing and ensuring data quality and sufficient data collection for use in data ecosystems.
Prior work supporting use-case owners to turn business questions into data-driven solutions.
Ability to advise on technology-specific qualification and upskilling needs.
Experience with product lifecycle ownership from requirements through implementation to problem resolution.
Understanding of market and technological trends in AI and data engineering.
Experience working with internal and external IT providers and vendors.
Desired Skills:
- AI engineering or data engineering
- product management or sub-product ownership
- agile teams (Scrum
