Job Title: Business Data & AI Specialist – GTM Data & Systems Strategy (Engineering Analyst IV) Location: Houston/Calgary (Hybrid – Wed. and Fri. remote) Duration: 12 months Department: Data & Systems Strategy

Role Summary: GTM D&SS is seeking a Business Data & AI Specialist to deliver applied data science, AI/ML, and automation solutions that support operational priorities including reliability, compliance, asset management, and decision support. This role will partner closely with operations, engineering, integrity, records, and asset management teams to translate business challenges into practical, data-driven solutions.

Key Responsibilities

Partner with stakeholders to identify, scope, and prioritize data and AI opportunities. Perform data acquisition, cleansing, transformation, and validation across structured/unstructured datasets. Design, build, and tune ML models (classification, regression, clustering, NLP). Build Generative AI and Agentic AI solutions, including prompt engineering and workflow automation. Deliver reproducible analyses and communicate findings to technical and non-technical audiences. Create business-facing dashboards and visualizations for decision-making. Write clean, well-structured Python code within shared repositories (Git). Support model deployment and operationalization with MLOps practices. Collaborate with D&SS, TIS, and domain experts to ensure solutions meet operational needs. Stay current on advances in data science, ML, and AI relevant to GTM operations.

Required Qualifications

Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or related field. 6–8 years of experience applying data, analytics, and AI/ML to business or operational problems in the energy industry. Strong proficiency in Python and common data science libraries. Solid understanding of applied ML concepts and statistics. Strong communication skills to present insights clearly to stakeholders. Experience collaborating across functions and working independently within scope.

Preferred Qualifications

Experience with Generative AI, LLMs, or agent-based workflows. SQL proficiency and experience with operational/analytical databases. Experience building dashboards/reports (Power BI). Familiarity with cloud platforms (Azure preferred; AWS/GCP acceptable). Background in engineering, operations, regulated, or energy sector environments. Exposure to documentation-heavy or audit-sensitive contexts.