Senior Data Analytical Specialist/Scientist

Job Title: Senior Data Analytical Specialist/Scientist
Location: Toronto, ON (Hybrid)
Estimated Duration: 6 Months

Job Title
Senior Data Analytical Specialist/Scientist
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.

Qualifications & Experience

• Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field, or equivalent experience.
• Significant experience in data science, advanced analytics, predictive modelling, machine learning, or statistical analysis.
• Strong proficiency in Python, SQL, statistical analysis, and machine learning techniques.
• Experience developing and validating predictive and machine learning models using real-world enterprise data.
• Knowledge of model evaluation, experimentation, feature engineering, data quality, and analytical methodology.
• Experience working with modern cloud-based data and analytics environments.
• Understanding of Generative AI and emerging AI techniques would be an asset.
• Strong business acumen with the ability to connect analytical findings to measurable business outcomes.
• Strong communication, problem-solving, and stakeholder-management skills.