Principal Data Scientist

Application deadline: 22.09.2026. We encourage candidates to apply as soon as possible.

About the role

We are seeking a Principal Data Scientist for our Houston team in Design, Software and Data Science (DSD), part of Technology, Digital and Innovation (TDI). The role works on key business challenges across Equinor, connecting traditional machine learning, mathematical optimization, reinforcement learning, decision intelligence and agentic AI with safe, scalable delivery in operational and business‑critical settings. As a principal data scientist you will provide professional technical leadership for highly complex tasks with strategic impact, combining deep hands‑on expertise with an enterprise perspective, sound judgement and the ability to align stakeholders around practical technical choices. Your work will help Equinor use AI responsibly to automate workflows, strengthen decisions and create measurable business value.

Responsibilities

• Drive complex AI deliveries from problem framing to implemented solution, including scope, priorities, delivery approach, technical quality and stakeholder alignment.
• Provide professional support to address key business issues, connecting optimization, reinforcement learning, forecasting and agentic AI to practical decisions in areas such as operations, engineering, energy markets, supply chain and maintenance.
• Manage uncertainty and non‑deterministic behavior by designing for bounded autonomy, confidence signaling, human oversight, auditable decisions, safe fallback and rollback paths.
• Improve performance, reliability and cost efficiency across development, evaluation and inference using techniques such as batching, caching, scalable serving, model routing, quantization and fit‑for‑purpose model selection.
• Combine agentic AI with mathematical optimization, reinforcement learning, Bayesian optimization or adaptive experimentation to support planning, scheduling, control, scenario exploration and decision support where relevant.
• Coach and advise colleagues on highly complex AI topics, helping teams handle ambiguity, adopt new technology and improve digital and analytical maturity.

Required Qualifications

• Master’s or PhD in operations research, applied mathematics, computer science, data science, control/automation, engineering or a related discipline.
• Solid experience and understanding of production‑grade AI/ML delivery, including data pipelines, model evaluation, software engineering practices, MLOps, cloud platforms and secure deployment.
• Ability to turn ambiguous business questions into analytical problems, delivery plans, decision recommendations and measurable outcomes.
• Strong professional depth in machine learning, mathematical optimisation, reinforcement learning, decision science, or advanced AI, with demonstrated ability to solve highly complex tasks.
• Experience leading technical tasks or work packages involving several contributors, stakeholders and dependencies, preferably in industrial, operational or enterprise‑scale environments.
• Strong stakeholder management and communication skills, with the ability to explain advanced technical concepts, influence across disciplines and facilitate decisions.
• Sound judgement on risk, safety, ethics, compliance and commercial value when applying AI to business‑critical processes.
• Domain understanding from energy production, logistics, power systems, process control, maintenance, trading, project execution or other complex industrial settings.

Preferred Qualifications

• Experience with optimisation solvers, stochastic or robust optimisation, Bayesian optimisation, multi‑objective trade‑offs, uncertainty quantification or sequential decision‑making.
• Experience combining optimisation or reinforcement learning with GenAI or agentic systems for planning, orchestration, scenario exploration or decision support.
• Experience with Azure, Databricks, Kubernetes, Python, CI/CD, MLflow or similar technologies used in scalable AI delivery.
• Knowledge of retrieval and knowledge systems, including vector databases, enterprise search and knowledge graphs.

What We Are Looking For

• A collaborative and structured data scientist who can combine deep technical expertise with business understanding, commercial awareness and strong execution discipline.
• Comfortable leading through influence, advising others, shaping best practice and delivering tangible improvements in a fast‑moving field.
• Alignment with Equinor’s values: open, collaborative, courageous and caring, with safety as a top priority and a commitment to a zero‑harm culture.

Benefits

• Comprehensive benefits package with competitive salary, global parental leave, bonus scheme and pension plan.
• Flexible work arrangements to support work‑life balance and personal well‑being.
• Opportunities for continuous learning and career development across multiple disciplines and geographies, including an internal job market.
• Inclusive culture that embraces differences and encourages employees to bring their whole selves to work.