We have a fantastic opportunity to deliver significant value across Shell by Autonomous Technical Reporting. TAO – TRDI offers an opportunity to provides this support and aspires to be a Trusted partner of Shell Assets helping them in their day-to-day issues through data diagnosis and co-creating insights. TAO – TRDI has started pilots for Autonomous MI which will enable asset stakeholders to analysis the data & build insights on the go.  

As part of the technical reporting opportunity realization journey play a key role as one of the levers of Transform accelerator by digitalizing, Standardizing, and replicating. Being a key enabler for TAO to support on Global digitalization initiatives includes but not limited to Asset Information Factory (AIF); HSSE Data & Analytics Platform (DAP); Subsurface Data Universe (SDU) and AMDP. Supports DIY Initiatives, help develop an Digitalization opportunity Funnel and Tracks Value through Digitalization.

Help build a unique team with hybrid capabilities by blending Process & AI skills not only to support the wide technical reporting portfolio but also to create a talent pipeline to TAO.

Purpose & Accountabilities

Supports to facilitate the Opportunity sessions within TAO and across Asset and to help build a Digitalization Opportunity Funnel.

Supporting Digitalization Lead for enabling TAO Digitalization needs to perform data diagnostics activities.

Provide integrated support options to businesses and functions (robust technical reporting with detailed analysis and improvement area identification)

Design, develop, and implement autonomous dashboards using GEN AI technologies.

Collaborate with cross-functional teams to understand business requirements and translate them into technical solution and with wider teams within Operational Excellence (Data Science, Automation, DQ etc.) in deploying reporting and analysis solutions.

Integrate data from various sources to provide comprehensive and actionable insights.

Work with IT and data governance teams to ensure compliance with data privacy and security regulations.

Experience in using digital tools and platforms for planning, scheduling, and executing maintenance activities is good to have. Has the ability to analyze maintenance data to optimize workflows and improve efficiency.

Understanding of reliability engineering principles, knowledge about reliability-centered maintenance (RCM) and failure modes and effects analysis (FMEA) would be an added advantage. Ability to leverage data analytics and machine learning to predict and enhance asset reliability.

Contribute to the overall digital transformation strategy of Shell by leveraging GEN AI capabilities.

Drive CI and contribute to TAO CI targets. Drive simplification and Integration beside Aggregation, Optimization and Automation of Technical Reporting

Coach, mentor, and sustain capability of building a hybrid skill of Business knowledge, Data diagnostic and Digital/AI together.  

Skills & Requirements

Individual contributor, playing critical role in Building DIY Digitalization solution within TAO and across assets.  

Plant or Industry experience would be an added advantage.

Graduate or master’s degree with ~7 years of IT Consulting Experience in Oil and Gas Industry.

Proficiency in GEN AI Technologies: Strong understanding of generative AI models and their applications in data visualization and analytics.

Machine Learning and Data Pre-processing:

Algorithms: Strong grasp of machine learning algorithms and their applications

Data Pre-processing: Techniques for cleaning, transforming, and preparing data for model training.

NLP (Natural Language Processing): Skills in processing and generating human language data[Text & Image].

Understanding of Large Language Models: GPT, BERT: Experience in working with and fine-tuning large language models

Data Integration: Experience in integrating data from multiple sources, including databases, APIs, and cloud services [Microsoft Azure/Databricks preferred]. Ensure seamless integration of real-time data from various sources to enhance decision-making processes.

Data Analytics: Perform advanced data analytics to derive actionable insights and support data-driven decision-making.

S4 Hana: Good to have experience in Integrating and leveraging S4 Hana for asset management.

Programming Skills: Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis.

Machine Learning: Knowledge of machine learning algorithms and their application in predictive analytics and data-driven decision-making.

Data Visualization: Strong skills in data visualization techniques to present complex data in an easily understandable format.

Project Management: Ability to manage multiple projects simultaneously and deliver results within deadlines.

Continuous Learning: A proactive approach to staying updated with the latest industry trends and technologies in digitalization and AI.

Communication: Strong verbal and written communication skills to effectively collaborate with stakeholders and present findings.