Stantec

Senior Data Scientist

Stantec

full-time

Posted on:

Origin:  • 🇺🇸 United States • Florida

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Job Level

Senior

Tech Stack

AWSAzureCloudETLGoogle Cloud PlatformPythonPyTorchScikit-LearnSparkSQLTableauTensorflow

About the role

  • Design and deliver end-to-end data science solutions, including predictive models, optimization algorithms, and decision-support dashboards.
  • Turn raw data into actionable insights supporting asset management, operations, and decision-making.
  • Work with clients to identify high-value use cases for AI/ML, data analytics, and digital transformation.
  • Develop data pipelines, statistical models, and machine learning workflows to address infrastructure, environmental, and operational challenges.
  • Collaborate with multidisciplinary teams of engineers, GIS specialists, and consultants to integrate analytics into enterprise workflows.
  • Translate complex datasets into compelling visualizations and narratives that drive decision-making.
  • Build, validate, and deploy models in production environments (cloud and on-premises), ensuring scalability and reliability.
  • Support business development activities including scoping, client presentations, and proposal development.

Requirements

  • Proficiency in Python (preferred), R, or similar languages for data science and machine learning.
  • Experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, or similar.
  • Strong data engineering skills (ETL pipelines, SQL, Spark, or cloud-native tools such as Azure Data Factory or AWS Glue).
  • Knowledge of cloud environments (Azure, AWS, GCP) and MLOps practices for deploying models.
  • Experience with geospatial analytics, spatial data processing, and GIS platforms (Esri preferred).
  • Ability to integrate analytics with business intelligence tools (e.g., Power BI, Tableau) for interactive insights.
  • Consulting experience with utilities, local governments, or public infrastructure agencies.
  • Understanding of digital transformation frameworks and how analytics supports organizational change.
  • Experience applying predictive analytics to asset management, operations optimization, or risk management.
  • Familiarity with asset lifecycle management, ISO 55000 principles, and performance-based decision-making.
  • Experience facilitating workshops or co-developing analytics strategies with clients.
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or related field (Master’s or PhD preferred).
  • 8+ years of progressive experience in data science, advanced analytics, or machine learning (consulting environment preferred).
  • Experience leading data science projects from ideation to deployment.
  • Prior experience working with public sector or utility clients is a plus.
  • Willingness/ability to travel up to 15% and valid driver’s license with satisfactory driving record.
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