Job Overview GTM D&SS is seeking a Business Data & AI Specialist to support the Gas Transmission business by delivering advanced data science, AI/ML, and automation solutions. The role focuses on solving real operational challenges—enhancing reliability, ensuring compliance, optimizing asset management, and improving decision‑making. Embedded within the D&SS team, the successful candidate will work closely with cross‑functional stakeholders including operations, engineering, integrity, records, and asset management, requiring a balance of strong technical expertise and business acumen to translate complex operational needs into practical, scalable, and auditable data‑driven solutions. Key Responsibilities Partner with stakeholders across operations, engineering, reliability, records, and asset management to identify and prioritize data and AI opportunities Translate business challenges and operational pain points into structured analytics and modeling problems Ensure solutions are aligned with operational realities, regulatory requirements, and business objectives Acquire, cleanse, transform, and validate structured and unstructured data from multiple sources Conduct exploratory data analysis to identify trends, anomalies, risks, and optimization opportunities Ensure data quality and integrity to support reliable insights Design, develop, validate, and optimize machine learning models (e.g., classification, regression, clustering, NLP) tailored to business use cases Develop Generative AI and Agentic AI solutions, including prompt engineering and workflow automation Apply appropriate evaluation techniques and document assumptions, limitations, and performance metrics Deliver reproducible, well‑documented analyses and models Clearly communicate insights, recommendations, and limitations to both technical and non‑technical audiences Create intuitive dashboards and visualizations that support operational and strategic decision‑making Support model deployment and operationalization in collaboration with D&SS and TIS teams Apply foundational MLOps practices, including monitoring model inputs, outputs, and performance over time Ensure solutions remain reliable, scalable, and maintainable in production environments Prepare and maintain comprehensive documentation to support knowledge transfer, auditability, and compliance Ensure adherence to coding standards, data governance, and security best practices Contribute clean, well‑structured Python code within shared repositories (Git) Identify opportunities to enhance existing analytics and AI solutions within the business Stay current on emerging data science, machine learning, and AI advancements relevant to operational contexts Promote the adoption of best practices and innovative approaches across teams Qualifications Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or a related field 6–8 years of experience applying data analytics, machine learning, and AI to solve business or operational problems Proven ability to translate business needs into actionable, data‑driven solutions Strong proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit‑learn) Solid understanding of applied machine learning techniques and statistical methods Experience with data preparation, feature engineering, and model evaluation Familiarity with version control systems (Git) and collaborative development practices Strong analytical thinking and problem‑solving skills Excellent communication skills, with the ability to present complex insights clearly and concisely Demonstrated ability to collaborate cross‑functionally beyond technical teams Ability to work independently while managing priorities within defined scope Strong attention to detail and commitment to delivering high‑quality, reliable solutions Preferred Skills Experience with Generative AI, Large Language Models (LLMs), or agent‑based systems Exposure to MLOps frameworks or model deployment pipelines Experience working in asset‑intensive or regulated industries (e.g., utilities, energy, infrastructure) Employment Note Successful applicants will be employees of Raise, working at Enbridge facilities with both Enbridge and contract employees. EEO Statement We value diversity and inclusion and encourage all qualified people to apply. #J-18808-Ljbffr