Data Scientist

FirePower Capital; Toronto; On-site; CAD 70,000 - 90,000; Full time

Job summary

A leading M&A advisory firm in Toronto is seeking a Data Scientist to join their Value Maximization team. The role focuses on analyzing business requirements and developing data strategies that enhance shareholder value. Candidates should have a strong foundation in data engineering, proficiency in Python and SQL, and experience with data visualization tools. This full-time role offers significant visibility and impact within a dynamic environment.

Qualifications

• Proficiency in Python and SQL, familiarity with data analysis libraries.
• Strong problem-solving skills and comfort with ambiguity.
• Excellent communication skills, especially with non-technical stakeholders.

Responsibilities

• Analyze business requirements and conceptualize a roadmap for implementation.
• Lead project delivery including scoping and task management.
• Build and deploy models, dashboards, and decision-support tools.

Skills

Data analysis

Python

SQL

Business acumen

Problem-solving

Communication

Machine learning

Data visualization

Cloud platforms

Education

Degree in Commerce, Math, Science, Engineering, Economics

Tools

Tableau

Power BI

pandas

NumPy

scikit-learn

Azure

AWS

Job description

About FirePower Capital

FirePower Capital is Canada’s go-to M&A advisory and private capital firm for entrepreneurs. Our Value Maximization (VMX) group is a data & AI SWAT team, transforming raw data into strategic firepower that drives enterprise value and protects the downside.

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.

Projects and Examples

• Analyze business requirements and conceptualize a roadmap for proper implementation of data capture, storage, cleaning/transformation, analytics and AI
• Design and automate data workflows that integrate/blend data from various systems/platforms and enable faster and more reliable insight
• Develop automated dashboards, algorithms, and scoring systems that drive tactical and strategic decisions across business functions, including lead qualification and ranking; customer segmentation and churn prediction; pricing optimization; operational benchmarking across multiple geographies; overall equipment effectiveness (OEE) analysis; staff performance benchmarking; inventory optimization; demand forecasting; market expansion prioritization; and financial process automation

Role & Responsibilities

The Data Scientist will be focused on driving significant value for our portfolio companies and advisory clients using data-driven techniques. This is a junior-to-mid-level role requiring ownership of end-to-end delivery of insights that increase shareholder value and inform strategy. 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.

Desired Skills and Aptitude

• Strong academic performance in Commerce, Math, Science, Engineering, Economics, or related fields.
• Quick learner with adaptability to new tools and business contexts.
• Entrepreneurial mindset with a bias toward action and real-world problem solving.
• Demonstrated business acumen and strategic thinking.
• Experience through internships, co-op, or academic projects in data science or analytics.
• Strong problem-solving skills and comfort with ambiguity.
• Organized, detail-oriented, and process-driven.
• Excellent communication skills, especially with non-technical stakeholders.
• Proficiency in Python and SQL; familiarity with pandas, NumPy, scikit-learn.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Familiarity with cloud platforms (e.g., Azure, Microsoft Fabric, AWS).
• Understanding of machine learning algorithms (e.g., k-NN, SVM, Decision Forests).
• Applied statistics knowledge (e.g., regression, distributions, hypothesis testing).
• Experience with data pipelining/orchestration tools
• Comfort working with scalable data architectures and systems.

The role reports to the Associate Manager, Value Maximization.