Senior Data Scientist
The Senior Data Scientist is a collaborative member of the Analytics team who creates value from data. They’re focused on identifying opportunities to drive value through advanced analytics, lead stakeholder engagements to assess analytical opportunities, and ensure value is delivered. Their technical accountabilities include the proactive retrieval of information from various sources and analysis to better understand business performance. The Senior Data Scientist builds data products that automate or optimize processes within the company, leading to improved business outcomes.
Security Requirements:
Successful applicants must have resided in Canada for a minimum of five (5) years to meet the requirements of the Canadian Controlled Goods Program (CGP), Canadian Government security clearances, and U.S. International Traffic in Arms Regulations (ITAR).
- Framing of analytics problems to drive value
- Assessment of opportunity ROI
- Developing the case for change
- Leading initiatives end to end
- Data Discovery, Sourcing and modeling
- Exploratory data analysis and feature engineering
- Algorithm selection, training, testing, and deployment
- Model deployment and maintenance
- Coach and mentor less experienced data scientists in the delivery of value through data science
- Responsible to provide solution recommendations/designs for their domain.
- University degree or college diploma related to Information Technology.
- 5+ years of experience applying statistical analysis, machine learning, forecasting, optimization, or related analytical techniques to solve business problems and deliver measurable outcomes.
- Expert-level proficiency in Python, SQL, and machine learning frameworks, with demonstrated experience designing scalable analytical solutions and deploying models into production environments.
- Experience leading complex analytical initiatives, establishing best practices, and guiding model development, monitoring, governance, and continuous improvement activities.
- Demonstrated ability to partner with senior business stakeholders to identify opportunities, translate business requirements into analytical solutions, and influence strategic decisions through data-driven insights.
- Experience with cloud-based AI platforms, MLOps, Generative AI, LLMs, Agentic AI, Azure AI services, or enterprise-scale AI architecture is strongly preferred.