Jobid=618234899987835304 (0.0989)
Imagine your career taking you to the depths of innovation and the heights of impact. Our people enable continuous progress. Their commitment, collective expertise, and unique capabilities are the engine room behind SBM Offshore’s – shaping the future of energy, and beyond.
About Us:
SBM Offshore is a global leader in deepwater ocean infrastructure, delivering floating production solutions across the full asset lifecycle—from design and construction to installation and operation. Supported by a global team of more than 8,000 professionals, the Company operates a long-term, asset-backed business model that delivers high-availability assets and predictable cash flows. SBM Offshore combines engineering expertise, operational reliability, and selective innovation to support safe, efficient, and lower-carbon energy production, while extending its capabilities into new opportunities across the blue economy.
Purpose
As a Senior Data Scientist, you contribute to the design and delivery of data‑driven and AI‑powered solutions within the SBM Offshore Data and Information Management Team. You collaborate closely with cross‑functional teams—including data scientists, business intelligence developers, data architects, data engineers, enterprise architects, and business stakeholders—to transform complex operational challenges into scalable solutions based on advanced analytics, machine learning, AI, and Generative AI models.
Responsibilities
Design, develop, industrialize, and maintain end‑to‑end data science and AI solutions across data preparation, modeling, validation, and lifecycle management, primarily using Azure‑based data and AI technologies.
Develop and evaluate advanced analytical models, including statistical methods, machine learning, deep learning, computer vision, and large‑scale document processing pipelines, aligned with business and technical objectives.
Contribute to Generative AI initiatives, such as LLM‑based solutions, document intelligence, copilots, and automation agents, in alignment with enterprise AI governance, security, and compliance standards.
Ensure production readiness through performance assessment, robustness checks, and application of MLOps best practices.
Collaborate with stakeholders to clarify business needs, define success criteria, and translate use cases into deployable analytics solutions.
Build clear reports, and technical documentation to communicate results to both technical and non‑technical audiences.
Work in an agile environment using tools such as Azure DevOps, Git, and cloud-native services.
Education
Master's or Engineering program in Data Science/Computer Science/Applied Mathematics/or a related quantitative field.
Solid academic background in mathematics, statistics, machine learning and software engineering.
Fluent in spoken and written English.
Experience
At least 5 years of experience as Data Scientist or similar position.
Proven experience developing Python-based data science and machine learning solutions.
Experience with Microsoft Azure (Azure ML, MS Foundry).
Experience with Generative AI, including LLMs, prompt engineering, RAG patterns, and AI governance considerations.
Experience in computer vision and/or large document processing (OCR, document classification, information extraction).
Experience with time series analysis, prediction, abnormal behaviors detection.
Familiarity with Git, CI/CD, and production-grade ML workflows
Oil & Gas domain experience is preferred.
Strong analytical mindset, autonomy, attention to detail, and a collaborative, stakeholder‑oriented approach.
Functional Competencies
Analytics and reportingIT Tools and applicationInspection, testing, commissioning and monitoringDigital savvyManagement of change applicationInnovationTechnical Data Management
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