Analyze marketing performance data to generate insights and develop data-driven strategies, acting as a consulting partner for clients.

Design, build, and deploy AI solutions using LLMs and other models. Collaborate with teams to enhance generative AI applications and ensure reliability in production.

Lead the Data Science team in developing LLM-powered solutions. Responsibilities include building and deploying AI systems, mentoring team members, and collaborating with cross-functional teams to deliver high-quality AI features.

The QA Engineer will ensure product quality by coordinating with teams, creating test plans, and mentoring junior engineers, while advocating for quality improvements.

The role involves designing and deploying AI solutions, integrating frameworks, applying MLOps practices, and collaborating with teams for software engineering.

The Platform Architect designs and integrates marketing, advertising, and customer experience technologies, leading a team to solve complex data challenges for clients.

Design and implement data solutions for marketing analytics, optimize data pipelines, and collaborate with teams for clean, reliable data workflows.

The Marketing Manager will develop and implement customer engagement marketing strategies for the Canadian Banking sector, focusing on revenue growth and client relationships through data-driven insights.

The Senior Data Engineer will design and build scalable data architectures and pipelines, ensuring data quality and collaborating with cross-functional teams.

The Senior Data Engineer will design and implement a data architecture for marketing, optimize data pipelines using Snowflake and Python, and support analytics efforts.

The Manager - Data Science leads hands-on AI/ML projects, mentors a data science team, and develops AI/ML solutions, ensuring timely delivery and scaling of capabilities.

Lead development of pricing optimization models using statistical and machine learning techniques. Analyze pricing elasticity, deploy models using AWS SageMaker, and utilize Bayesian modeling to inform business decisions.

The Senior Data Scientist will lead pricing optimization projects, analyze pricing elasticity, and deploy machine learning models using AWS SageMaker, focusing on Bayesian modeling and collaboration with cross-functional teams.

Lead AI and data science projects, mentor a team, collaborate with stakeholders, ensure project quality, and deliver insights for decision-making.

The Manager of Digital Messaging is responsible for coordinating digital marketing campaigns, ensuring compliance, optimizing customer engagement, and project management.

Lead end-to-end BI projects, developing impactful Power BI dashboards and collaborating with clients and stakeholders to deliver actionable insights.

Lead and execute GA4 technical implementations, focusing on mobile app analytics, debugging issues, and collaborating with teams to ensure data accuracy and governance.

The Senior Data Engineer will design and implement data architecture, optimize data pipelines, support data modeling, and ensure reliable data flows for analytics and reporting.

Lead complex IT projects with a focus on AI implementations. Manage project delivery, Agile processes, and cross-functional collaboration while ensuring alignment with organizational goals.

The Lead AI Engineer will design, implement, and optimize AI-driven solutions on AWS, focusing on financial services while ensuring system scalability and performance.