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 Robust 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 #J-18808-Ljbffr

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