Job DescriptionJob Description

Job Title: Data Analytical Specialist / Scientist - Senior

Location: Toronto, Ontario, Canada

Work Model: Hybrid

Duration: 6 months

Must Haves

- Deep expertise in statistics, probability, predictive modelling and machine learning, including classification, regression, clustering, feature engineering, experimentation, model selection, validation, bias/variance, overfitting and statistical inference.
- Advanced hands-on proficiency in Python, SQL and ML frameworks, with demonstrated experience building, tuning and validating models using real-world datasets. Tech stack: Python, SQL, Power BI, VSCode, Git, Jira, Azure (OpenAI, Foundry and ML Studio), Databricks.
- Strong hands-on experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry, including end-to-end ML pipelines covering experimentation, training, evaluation and operationalization.

Description / Responsibilities / Skills

Description

- The Senior Data Analytical Specialist/Scientist will develop advanced analytics, predictive models, and AI-driven insights to address priority business opportunities.

Key Responsibilities

- Conduct exploratory data analysis to identify patterns, trends, relationships, and opportunities for improved decision-making.




- Translate business problems into appropriate analytical and modelling approaches, defining hypotheses, methodologies, and success measures.
- Assess the quality, availability, and readiness of data required for AI and advanced analytics use cases.
- Support enterprise data maturity and analytics capability assessments and identify opportunities for improvement.
- Partner with business stakeholders to identify high-value AI and analytics opportunities and assess potential business value and feasibility.
- Develop prototypes and proofs of concept to test analytical approaches before broader implementation.

Key Responsibilities (continued)

- Work closely with Data Engineers, Data Architects, Product Managers, and technology teams to operationalize successful models and analytical solutions.
- Define and monitor analytical KPIs and support evaluation of whether delivered solutions achieve intended business outcomes.
- Communicate complex analytical findings and recommendations in explicit, actionable terms for both technical and executive audiences.
- Apply appropriate Responsible AI, privacy, data governance, and model risk considerations throughout the analytics lifecycle.

📌 Data Analytical Specialist/Scientist - Senior (Toronto)
🏢 Innosystech
📍 Toronto