Data Scientist

Waste Connections

About The Position

Waste Connections is seeking a Data Scientist to join our growing Analytics & AI team. This role will partner with business leaders to solve complex operational and strategic challenges through analytics, machine learning, data engineering, and AI-driven solutions. The ideal candidate is a hands-on problem solver who can translate business needs into actionable insights and production-ready solutions. This position requires a blend of technical expertise, business acumen, and strong communication skills, with ownership spanning the full lifecycle from data exploration and model development to deployment and adoption.

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or related quantitative field
3+ years of experience in Data Science, Machine Learning, Analytics, or a related discipline
Strong proficiency in Python and SQL
Experience building and deploying production machine learning or analytics solutions
Experience developing and maintaining data pipelines
Strong knowledge of statistics, hypothesis testing, and model evaluation techniques
Experience communicating analytical findings to business stakeholders
Excellent problem-solving, analytical, and communication skills

Nice To Haves

Experience with Databricks, Spark, or PySpark
Experience with cloud platforms such as AWS or Azure
Experience with Tableau, Power BI, or other data visualization tools
Experience with modern data architectures and lakehouse environments
Experience developing AI-enabled applications
Familiarity with forecasting, optimization, customer analytics, pricing, or operational analytics

Responsibilities

Partner with business stakeholders to identify opportunities for analytics, automation, and AI solutions
Develop, deploy, and maintain machine learning models and advanced analytics solutions
Design and build scalable data pipelines and data products
Perform data analysis, feature engineering, forecasting, and statistical modeling
Create dashboards, reports, and self-service analytics tools to support decision-making
Monitor, improve, and support production analytics solutions
Present findings and recommendations to both technical and non-technical audiences
Drive measurable business impact through data-driven insights and operational improvements
Collaborate with data engineers, analysts, and technology teams on enterprise initiatives

Benefits

Opportunity to work on high-impact business problems
Exposure to analytics, machine learning, data engineering, and AI initiatives
Direct interaction with business leaders and decision-makers
Ownership of projects from concept through production deployment
Collaborative team environment with strong opportunities for growth and development

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