Upstream optimization, an innovative division of the Rosenxt Group, which was spun off in 2023 and is dedicated to expanding into new business areas. Our focus is on developing advanced technologies for the optimization of energy production. Our state-of-the-art flow measurement device is a clamp-on non-intrusive system, gathering extensive real-time operational process data. In our interdisciplinary, agile, and autonomous teams, we foster innovations and customer value.
As Product Owner, you lead the development of our AI-driven reservoir simulator. This next-generation digital product combines machine learning with real-time and historical production data to model, predict and optimize reservoir performance. You connect reservoir engineers, data scientists, software developers and business stakeholders, and you turn complex technical and commercial requirements into a clear, prioritized product backlog and roadmap.
What you can expect
-
Own and continuously refine the product vision, roadmap, and backlog for the AI-driven reservoir simulator, aligned with business goals and market demands.
-
Translate reservoir engineering and production-optimization requirements into clear user stories, acceptance criteria, and well-defined epics for cross-functional development teams.
-
Collaborate closely with reservoir engineers, data scientists, and software/DevOps teams to ensure the AI model architecture is developed with production-grade data pipelines and validated against real reservoir behavior
-
Define and prioritize features covering data ingestion and preprocessing (data cleaning, integration, transformation, aggregation of high-frequency sensor and low-frequency reservoir data), model training, history matching, and production forecasting and further reservoir optimization features.
-
Facilitate sprint planning, backlog refinement, reviews, and retrospectives in an agile/Scrum environment in alignment with the extended project team; track progress against OKRs and epics.
-
Act as the primary point of contact between internal stakeholders (engineering, commercial, leadership) regarding product scope, timelines, and value delivery.
-
Define and monitor KPIs for model accuracy, computational performance, and business value (e.g., incremental production, reduced simulation runtime, improved forecast accuracy).
-
Stay current on AI/ML advances in reservoir simulation (e.g., neural network surrogates, generative AI assistants, automated history matching) to keep the product roadmap competitive.