Live opening · Posted 3 days ago

Senior Data Scientist

TechBlocks · Vaughan, ON (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyTechBlocks
LocationVaughan, ON (Remote)
Salary85 CAD/hr - 90 CAD/hr
Work modeYes
SkillsPython, Azure
SourceLinkedin
ListedPosted 3 days ago

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About the role

Description supplied by the original job listing.

Job Title: Senior Data Scientist
Location: 399 Applewood Crescent, Vaughan
Role Overview
We are seeking a Senior Data Scientist with strong expertise in optimization and applied machine learning to support the development of large-scale decision systems in supply chain operations, including routing, scheduling, and resource allocation.
This is a hands-on, execution-focused role working under the Data Science Lead. The successful candidate will own and enhance components of analytical and optimization models, ensuring they are scalable, reliable, and aligned with business needs. The role requires the ability to connect business requirements with data science solutions, operate in a fast-paced environment, and communicate effectively with both technical and non-technical stakeholders.
Key Responsibilities
Develop and enhance optimization models using MILP and heuristic approaches, applying them to problems such as vehicle routing, scheduling, and resource allocation, and improving performance using solvers such as Gurobi
Apply machine learning techniques to support decision systems, including predictive modeling, feature engineering, and generating inputs for optimization models, while ensuring strong integration between ML and optimization frameworks
Translate business requirements into structured analytical and optimization problems, incorporating operational constraints and clearly communicating model assumptions, trade-offs, and outcomes to stakeholders
Diagnose and resolve model issues including infeasibility, performance bottlenecks, and data inconsistencies, while analyzing trade-offs across cost, service level, and operational feasibility
Develop and maintain data workflows using Python and SQL, and support scalable processing and deployment within cloud environments such as Azure and Databricks
Ensure data quality and model reliability by validating inputs, identifying gaps, and supporting feedback loops to improve model accuracy and alignment with operations
Collaborate with cross-functional teams, take ownership of model components, contribute to technical design discussions, and provide guidance to junior team members
Qualifications
8–15+ years of experience in data science, operations research, or a related field
Strong hands-on experience in optimization (e.g., MILP, VRP, scheduling) and machine learning
Proficiency in Python and SQL
Experience working with optimization solvers such as Gurobi
Familiarity with Azure and Databricks environments
Proven ability to translate business problems into data-driven solutions
Strong problem-solving skills and ability to work in fast-paced environments
Effective communication skills with both technical and business stakeholders
Preferred Qualifications
Experience in supply chain, logistics, or operations-focused environments
Familiarity with large-scale optimization techniques or heuristic methods
Experience working with distributed data systems or cloud-based analytics platforms
What Success Looks Like
You will deliver reliable and scalable model components that drive operational decisions, effectively bridge the gap between business and analytics, and contribute to measurable improvements in efficiency, service levels, or cost.
Compensation:
Pay Range: $85 - $90/HR CAD
Why TechBlocks
Work directly with Fortune 500 executives and digital transformation leaders.
Be part of a fast-growing, AI-native software engineering firm redefining global delivery through our GCC-as-a-Service model.
Collaborate with global teams in Canada, the U.S., and India on cutting-edge cloud and AI initiatives.
Competitive compensation, performance incentives, and a culture that values ownership, agility, and innovation.

Work arrangement
Yes

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