Data Scientist / ML Engineer

Enbridge

Data Scientist/ML Engineer developing production-ready machine learning and analytical solutions for Enbridge’s energy infrastructure operations. Leading initiatives from discovery through deployment and continuous improvement.

Posted 9/9/2026full-timeCalgary • 🇨🇦 CanadaMid-LevelSenior💰 $96,200 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in statistical analysis, machine learning, and software engineering practices, with a strong focus on delivering data-driven solutions and operationalizing analytical initiatives. Proficient in Python, SQL, and enterprise platforms like Databricks, with a solid foundation in model validation and uncertainty assessment.

Highest-signal resume keywords

Machine Learning Solutions DeliveryStatistical AnalysisPython ProficiencyDatabricks ExperienceMLOps Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningStatistical AnalysisModel ValidationUncertainty AssessmentPythonSQLData Science LibrariesSparkPySparkMLflow

Soft Skills

CommunicationCollaborationInfluencing Technical DecisionsGuiding Multidisciplinary ContributorsAnalytical Interpretation

Tools & Technologies

DatabricksSparkPySparkMLflow

Certifications & Qualifications

Valid Passport

Industry Keywords

Data ScienceMachine LearningMLOpsStatistical SolutionsAnalytical Initiatives

Tech Stack

Tools & technologies

PySparkPythonSparkSQL

About the role

Key responsibilities & impact

Partner with business stakeholders, engineers, and subject-matter experts to define complex problems, requirements, and success criteria
Assess data and technical feasibility, dependencies, risks, integration needs, and opportunities
Plan and lead analytical initiatives from discovery and proof of concept through MVP, production deployment, and ongoing enhancement
Design, develop, validate, and operationalize statistical, machine learning, simulation, and optimization solutions
Apply software engineering, MLOps, and Responsible AI practices
Provide technical direction, coordinate contributors, review deliverables, and remain involved in hands-on development
Communicate analytical findings, assumptions, limitations, and evidence-based recommendations
Collaborate with stakeholders, engineers, subject-matter experts, and multidisciplinary technical teams across iterative delivery stages

Requirements

What you’ll need

Degree in computer science, engineering, mathematics, statistics, operations research, data science, or a related quantitative discipline
Six or more years of related experience, including significant hands-on experience delivering data science or machine learning solutions
Strong knowledge of statistics, machine learning, model validation, uncertainty assessment, and analytical interpretation
Proficiency in Python and SQL
Experience with established data science and machine learning libraries
Hands-on experience with Databricks or a comparable enterprise platform, including Spark or PySpark, MLflow, and production-focused machine learning development
Experience engineering, deploying, and managing analytical solutions throughout their lifecycle
Ability to learn complex subject areas, guide multidisciplinary contributors, influence technical decisions, and communicate recommendations clearly
Ability to travel throughout North America (US and Canada) for business purposes
Valid passport required
Final candidates may be required to undergo security screening, including a criminal records check

Benefits

Comp & perks

Flexible benefits program covering health, dental, insurance, and disability
Up to 20 weeks of paid leave for birth-giving parents and up to 12 weeks for other eligible parents
Retirement savings plans, including a savings plan with company stock as an investment option
Paid time off, vacation, sick leave, paid personal days, and paid holidays
Employee and Family Assistance Program
Wellness Program supporting physical, mental, social, and financial well-being
FlexWork hybrid options, including working from home on Wednesdays and Fridays, compressed work week schedules, or flexible start and end times