Sr Exp Data Science&Artif Intelligence

Your tasks

• Analyze operational, financial, safety, and maintenance data across systems to uncover patterns and build predictive models that improve uptime, efficiency, and risk management.
• Understand both the Operational challenges and the rationale behind the Digital Neptun Business case – and based on both, support the HoD Operations Excellence in delivering Asset value improvements in terms of safety, efficiency and production uptime.
• Develop data driven models supported by AI or machine learning to be contextualized via dashboards that dynamically adjust to user needs, enabling smarter, faster decisions at every level of the organization.
• Anticipate equipment failures in wells and facilities using machine learning, reducing downtime and optimizing maintenance strategies.
• Identify inefficiencies across production and support processes, delivering actionable insights that drive continuous performance improvement.
• Partners with the Sr Expert Business Analytics, Sr Expert Products Owner, and Sr Expert Integrated Workflow Engineering to incorporate data-driven enhancements into user stories and use cases, focusing on AI models that improve feature utilization, predictive capabilities, and overall optimization and value of the digital Neptun.
• Apply AI and computer vision to automate safety checks, detect hazards, and ensure quality in processing environments.
• Manage and refine large, complex datasets within the Neptun application portfolio, ensuring high-quality inputs for reliable analytics and modeling.

Your profile

• Education: University degree in Engineering (Petroleum, Chemical, Mechanical or Industrial), Computer Science or Business Administration
• Relevant professional experience: >7 years
• Experience with industrial data historians (e.g., Aveva PI, IP21)
• Familiarity with ETL pipelines and tools like Azure Data Factory or Microsoft Fabric
• Proficiency in SQL, Python, and Spark for data wrangling
• Supervised and unsupervised learning (e.g., regression, clustering, reinforcement)
• Time-series analysis for predictive maintenance and process optimization
• Model validation and performance tuning in noisy, sensor-driven environments
• Building dashboards in Power BI, Grafana, etc
• Communicating insights to non-technical stakeholders in operations and engineering
• Proficient in English