Specialist I TIS Data Scientist / ML Engineer at Enbridge in Calgary, AB

Job description

Posting End Date: September 25, 2026 Employee Type: Regular-Full time Union/Non: This is a non-union position At Enbridge, you can apply advanced technology to meaningful challenges while building a career in a workplace grounded in safety, innovation, and collaboration. As a Specialist I, TIS Data Scientist / ML Engineer, you will lead the development and delivery of advanced analytical solutions for complex business and operational challenges. Working closely with stakeholders, engineers, and subject-matter experts, you will shape problems into actionable solutions and guide initiatives from early discovery and proof of concept through production and ongoing enhancement. This is an opportunity to combine technical leadership with hands-on development, influence decisions through data, and advance responsible, scalable machine learning and AI solutions that make a meaningful impact. If you are ready to apply your data science and machine learning expertise to complex, meaningful challenges, we invite you to join Enbridge and help shape responsible, production-ready analytical solutions that create lasting impact. What You Will Do: Partner with business stakeholders, engineers, and subject-matter experts to define complex problems, solution requirements, and measurable success criteria. Assess data and technical feasibility, identifying critical dependencies, risks, integration needs, and opportunities early in the solution lifecycle. Plan and lead analytical initiatives from discovery and proof of concept through minimum viable product, production deployment, and ongoing enhancement. Design, develop, validate, and operationalize statistical, machine learning, simulation, and optimization solutions that align with business and operational needs. Apply strong software engineering, MLOps, and Responsible AI practices to create reproducible, maintainable, and supportable solutions. Provide technical direction while coordinating contributors, reviewing deliverables, and remaining actively involved in hands-on development. Communicate analytical findings, assumptions, limitations, and evidence-based recommendations in a way that supports informed decision-making. Who You Are: You have a degree in computer science, engineering, mathematics, statistics, operations research, data science, or a related quantitative discipline. You bring six or more years of related experience, including significant hands-on experience delivering data science or machine learning solutions in business or operational environments. You have strong knowledge of statistics, machine learning, model validation, uncertainty assessment, and analytical interpretation. You are proficient in Python and SQL and have experience using established data science and machine learning libraries. You have hands-on experience with Databricks or a comparable enterprise platform, including Spark or PySpark, MLflow, and production-focused machine learning development. You have experience engineering, deploying, and managing reliable analytical solutions throughout their lifecycle, from discovery and experimentation through production and continuous improvement. You are skilled at learning complex subject areas, guiding multidisciplinary contributors, influencing technical decisions, and communicating recommendations clearly to technical and non-technical audiences. Able to travel throughout North America (US and Canada) for business purposes. Valid passport is required. Preferred: Forecasting, anomaly detection, predictive maintenance, optimization, simulation, physics-informed machine learning, computer vision, natural language processing, or generative AI. Midstream operations, pipelines, hydraulic modelling, industrial operations, asset management, or another physical asset-intensive environment. Working with operational time-series data from SCADA, historians, sensors, or IoT systems. Combining engineering or physical-system knowledge with statistical or machine learning te