HSE Expert (Oil & Gas) — Digital Platform & AI Use Case Delivery Dicetek LLC

We need an HSE professional with 5–10 years of operational Oil & Gas experience who can act as the functional bridge between the business and the technical build team. They DO NOT need to code—but they must be able to translate HSE requirements into technical inputs, validate model outputs, and work closely with the delivery team throughout build and rollout. This role supports AI-enabled use case development across the full value chain (upstream, midstream, downstream). Key strength is industry credibility + structured analytical thinking + strong documentation. Arabic optional; English required. No certifications required beyond core HSE experience.

Experience

• 5–10 years HSE experience within Oil & Gas (operations, projects, or integrated company experience all acceptable)

• Must have firsthand exposure to typical HSE workflows such as:

  • Incident reporting & investigation (RCA)

  • Permit-to-Work (PTW)

  • Job Safety Analysis / Task Risk Assessment

  • SIMOPS

  • Contractor HSE

  • Leading/lagging indicators

• Experience working with digital or data teams preferred, but not required if the candidate demonstrates strong analytical ability and structured communication.

Functional Strengths to Look For

• Can clearly articulate how HSE processes work in reality (field-level understanding).

• Can describe typical operational pain points, data gaps, and risk areas.

• Understands incident taxonomies, hierarchy of controls, and barrier management concepts.

• Comfortable documenting detailed requirements, writing use-case descriptions, and supporting UAT.

• Able to engage credibly with stakeholders across field HSE, operations, and leadership.

Technical/Digital Expectations (Non-Coding)

Look for candidates who can:

• Work with data/AI teams to define features, validate model outputs, and challenge assumptions

• Understand basic analytics concepts (metrics, data quality, dashboards, classification)

• Participate in end-user testing and assess whether outputs make sense operationally

• Translate feedback from business users into clear improvements for developers

They do not need to be a data scientist, developer, or ML engineer.