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 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
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