Senior Data Analytical Specialist/Scientist JP242

P@thlion Staffing Careers; Toronto; On-site; CAD 110,000 - 160,000; Full time

Job summary

P@thlion Staffing Careers seeks a Senior Data Analytical Specialist/Scientist to design and deploy advanced analytics, predictive models, and AI-driven insights addressing priority business opportunities. The role applies statistics, machine learning, and data analysis across enterprise data to support data maturity and value realization.

The candidate will partner with data engineers, product managers, and technology teams to operationalize models, monitor KPIs, and present findings to

Responsibilities

• Design and develop advanced analytics, predictive models, and machine learning solutions for priority business use cases.
• Conduct exploratory data analysis to identify patterns, trends, relationships, and opportunities for improved decision-making.
• Translate business problems into 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.
• Validate model performance using appropriate statistical and machine learning techniques and communicate model assumptions, limitations, and results.
• 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.
• 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 clear, actionable terms for both technical and executive audiences.
• Apply appropriate Responsible AI, privacy, data governance, and model risk considerations throughout the analytics lifecycle.

Job description

The Senior Data Analytical Specialist/Scientist will develop advanced analytics, predictive models, and AI-driven insights to address priority business opportunities. The role will apply statistical, machine learning, and analytical techniques to enterprise data, while supporting data maturity assessments, model validation, business-value analysis, and the identification of high-value AI and analytics opportunities.

Key Responsibilities

• Design and develop advanced analytics, predictive models, and machine learning solutions for priority business use cases.
• 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.
• Validate model performance using appropriate statistical and machine learning techniques and communicate model assumptions, limitations, and results.
• 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.
• 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 clear, actionable terms for both technical and executive audiences.
• Apply appropriate Responsible AI, privacy, data governance, and model risk considerations throughout the analytics lifecycle.