Senior Data Analytical Specialist/Scientist JP242
P@thlion Staffing Careers • Toronto, ON, Canada
Il y a 9 heures
Type de contrat
- Temps plein
- Quick Apply
Description de poste
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.