- 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 - 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 - Solid 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 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 Delivery - Statistical Analysis - Python Proficiency - Databricks Experience - MLOps Practices Hard Skills - Machine Learning - Statistical Analysis - Model Validation - Uncertainty Assessment - Python - SQL - Data Science Libraries - Spark - PySpark - MLflow Soft Skills - Communication - Collaboration - Influencing Technical Decisions - Guiding Multidisciplinary Contributors - Analytical Interpretation Certifications & Qualifications - Valid Passport Industry Keywords - Data Science - Machine Learning - MLOps - Statistical Solutions - Analytical Initiatives Tools & Technologies - Databricks - Spark - PySpark - MLflow

📌 Data Scientist / ML Engineer (Calgary)
🏢 Jobtailor
📍 Calgary