About the role
Data Scientist for Value Maximization
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.
Some relevant examples of projects are:
- 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
- • 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.
About the role
Data Scientist for Value Maximization
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.
Some relevant examples of projects are:
- 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
- • 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.