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

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

Demonstrates expertise in statistical analysis, machine learning, and software engineering practices, with a solid 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