Business Data Analyst - Artificial Intelligence; AI/ML
Job in
Toronto, Ontario, C6A, Canada
Listed on 2026-06-19
Listing for:
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Full Time
position Listed on 2026-06-19
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist, Data Analyst
Job Description & How to Apply Below
Job Title:
Senior Business Analyst – Artificial Intelligence (AIML)
Location:
Toronto, ON
Work Style:
Hybrid (2 days onsite preferred)
- Business Analysis
- Machine Learning
- Artificial Intelligence (AI)
8-10 Years
OverviewWe are seeking a highly experienced AI-focused Business Analyst to drive the identification, analysis, and implementation of Artificial Intelligence and Machine Learning solutions across the organization. This role bridges the gap between business objectives and data science/engineering teams, ensuring AI initiatives deliver measurable business value, ethical compliance, and scalability.
Key Responsibilities- Identify and evaluate AI/ML use cases aligned with business goals (e.g., predictive analytics, NLP, computer vision).
- Collaborate with leadership to define AI strategy and roadmap.
- Conduct feasibility analysis including cost-benefit, ROI, and risk assessment.
- Recommend AI-driven solutions to improve efficiency, decision‑making, and customer experience.
- Elicit and document AI‑specific functional and non‑functional requirements.
- Translate business problems into data science problems and hypotheses.
- Define:
- Model inputs/outputs
- Training data requirements
- Performance metrics (accuracy, precision, recall, etc.)
- Develop user stories, epics, and AI use case documentation.
- Analyze data sources to assess:
- Data availability, quality, and readiness
- Data governance and compliance requirements
- Collaborate with data engineers to define:
- Data pipelines
- Data cleaning and transformation needs
- Support creation of data dictionaries and metadata documentation.
- Work closely with:
Data Scientists, Machine Learning Engineers, Data Engineers. - Facilitate understanding of business context for model development.
- Ensure models align with business needs and operational constraints.
- Participate in model evaluation, validation, and performance monitoring discussions.
- Support end‑to‑end lifecycle:
Problem definition, Model development, Testing & validation, Deployment & monitoring. - Define acceptance criteria for AI models.
- Ensure continuous improvement using feedback loops and retraining strategies.
- Ensure AI solutions comply with data privacy regulations (GDPR, CCPA).
- Ensure compliance with ethical AI principles (fairness, bias mitigation, transparency).
- Assist in defining model explainability and auditability requirements.
- Support risk management for AI‑based decisions.
- Integrate AI models into business workflows and applications.
- Define target operating models (TOM) for AI adoption.
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