Data Scientist at FirePower Capital
Toronto, ON M5E 1B3, Canada -
Full Time


Start Date

Immediate

Expiry Date

18 Nov, 25

Salary

0.0

Posted On

19 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Power Bi, Pandas, Dashboards, Internships, Models, Data Science, Enrichment, Knowledge Sharing, Data Mining, Classification, Business Strategy, Commerce, Aws, Analytics, Numpy, Project Delivery, Hypothesis Testing, Economics, Integration, Optimization, Data Collection

Industry

Information Technology/IT

Description

How To Apply:

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Responsibilities

THE ROLE:

This is a rare opportunity to join a fast-moving, commercially minded team that blends deep technical expertise with sharp business instincts. As a Data Scientist on the VMX team, you’ll work directly with entrepreneurial companies and senior executives, helping them make smarter, data-driven decisions - whether they’re preparing for a sale, scaling operations, or navigating complex market dynamics.
We’re looking for a Data Scientist with a strong foundation in data engineering and analytics. Your focus will be on analyzing business requirements, preparing and transforming data, and visualizing insights in a way that resonates with non-technical stakeholders. This is a full-time role with high visibility and impact.

You’ll collaborate with other stakeholders across the firm and contribute to internal knowledge sharing and documentation.

  • Lead project delivery with support, including scoping, task management, and client communications.
  • Evaluate client infrastructure and data assets to develop tailored data maturity roadmaps.
  • Design scalable data architectures and pipelines aligned with business goals.
  • Build and deploy models, dashboards, and decision-support tools that drive measurable outcomes.
  • Translate complex findings into actionable insights for executive stakeholders.
  • Enhance data collection and enrichment, including integration of external sources.
  • Cleanse, process, and validate data across internal and external systems.
  • Conduct ad-hoc analysis and present results clearly to non-technical audiences.
  • Build API integrations and automate data ingestion workflows.
  • Conduct data mining and exploration using machine learning techniques for classification, prediction, and optimization.
  • Collaborate cross-functionally to align data initiatives with business strategy.
  • Contribute to internal documentation, best practices, and reusable assets
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