Top Data Jobs in Ottawa

The Senior Data Engineer at ClickUp will design and maintain cloud-native data infrastructure, develop data pipelines, automate deployments, and work with cross-functional teams to enhance data solutions while mentoring peers.

The Associate Director of Data & AI will lead transformation programs, drive business value through AI strategies, and oversee modern data platform delivery for major enterprises.

As a Data Scientist at Lighthouse, you'll develop and implement ML and AI techniques, influencing key product features and enhancing personalization for hotels globally.

The role involves designing data pipelines and models for Stripe's Growth and Marketing teams, ensuring data integrity and performance metrics. Collaboration with various teams to enhance data visibility and support is crucial.

As a Product Manager at Qohash, you'll lead the development of data-centric cybersecurity solutions, ensuring alignment with customer needs and strategic company goals. Your role includes managing the product lifecycle, collaborating with cross-functional teams, and leveraging AI tools for efficiency.

The Staff Data Engineer will lead the technical vision and architecture of data engineering, develop pipelines, and mentor junior engineers while working with cloud environments and various data tools.

As a Senior Engineer on the Data Platform team, you will design and build data pipelines and optimize storage systems to enhance analytics and machine learning capabilities.

The Senior/Lead Data Scientist will develop advanced forecasting models, collaborate with business partners, and guide a team in deploying analytical solutions.

The Senior Data Platform Engineer will manage and develop the data infrastructure on Databricks and AWS, ensuring scalable and efficient data capabilities while collaborating across teams.

As a Data Analyst, you will help understand player behaviors using SQL, perform analyses, create dashboards, and promote data-driven decisions.

The Data Analyst will engage in preparing and understanding data for predictive modeling, collaborate with cross-functional teams, create datasets, and manage data assets with an aim to innovate and drive productivity.

Lead Data Scientist responsible for driving measurable outcomes through experiments, data analysis, and creating metrics to track performance. Collaborate with engineering for productionizing models and enhancing recommendation systems using AI technologies.

Responsible for database administration, data engineering, and operations within the Data Lake and Data Warehouse. Lead ETL design, troubleshoot production issues, and mentor junior engineers.

Build and maintain production data pipelines (ingress/egress) into BigQuery, implement data quality/freshness checks and monitoring, maintain ingestion frameworks and dbt source/staging layers, troubleshoot pipeline issues, document systems, and help productionalize ML pipelines and event-driven data processes while collaborating with finance, revenue, and analytics teams.

As a Data Annotation Specialist, you will label, audit, and optimize data for AI models in Chinese while ensuring high accuracy and quality. You will perform repetitive tasks and collaborate with teams, providing feedback and recommendations for data improvement.

The Data Platform Marketing Manager will lead marketing strategies for DoiT's data lake and Snowflake optimization business, aiming to drive growth and impact.

The Senior Product Data Analyst will analyze data to support product development, present insights, and drive data-driven decisions for marketing campaigns.

You will architect and develop new features for SELECT, focusing on cost management, UI components, data visualization, and improving application performance.

The Senior Product Manager will enhance the Parameters Service and develop an Information Requirements application for Autodesk, focusing on data consistency and communication among AEC stakeholders while ensuring product delivery and alignment with customer needs.

This role involves deploying solutions for clients, managing data compliance, and providing feedback for product improvement. Requires collaboration with teams and clients.

The role involves owning the complete data science lifecycle from analysis to model deployment, focusing on logistics-related predictive models and collaborating with an ML Engineer.

The Principal Data Strategist will lead data strategy engagements, aligning data initiatives with business goals, facilitating stakeholder alignment, and designing governance frameworks while driving account growth and advancing the practice within Caylent.

Seeking an experienced Data Scientist to develop forecasting models, collaborate with business partners, and lead end-to-end model development using PySpark, Databricks, and Azure.

Develop and implement fraud detection models using machine learning techniques, analyze data for patterns, and optimize existing models for risk management.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.