Top Data Jobs in Ottawa

Audit and improve data labeling quality in human-in-the-loop ML workflows. Coach and onboard labelers, provide actionable feedback, monitor queues, identify recurring issues, and help refine guidelines and processes.

Evaluate AI outputs and audit model behavior, apply and refine guidelines, identify failure modes and trends, document findings, and collaborate with leads and cross-functional teams to improve evaluation frameworks and data quality.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, enforce and improve guidelines, identify recurring issues and edge cases, escalate risks, and document feedback to support human-in-the-loop AI workflows.

Evaluate AI model outputs, perform audit-based reviews, apply and refine guidelines, identify performance trends and failure modes, document findings, and collaborate with cross-functional teams to improve model evaluation and data quality.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, apply and refine guidelines, monitor workflows and escalate issues, document findings, and support human-in-the-loop AI evaluation processes.

Build and maintain scalable, reliable data systems and pipelines, uphold SLOs, partner with Product/Sales/Finance, enable self-service analytics, contribute to data platform strategy, and improve engineering practices for testing, reliability, and documentation.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

The Data Engineer will analyze and interpret data to drive insights, create dashboards, and enhance product performance, collaborating with cross-functional teams.

As a Data Analyst, you will analyze user behavior and product performance, creating reports and dashboards to aid decision-making and optimize user experience.

Build, deploy, and iterate predictive models and real-time scoring pipelines using behavioral and clickstream data to improve lead quality and campaign optimization. Collaborate with marketing, media buying, and analytics teams to translate business needs into hypotheses, perform exploratory analysis, monitor model performance, and communicate statistically rigorous insights to non-technical stakeholders.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

The Senior Geo Data Scientist will develop advanced machine learning models for geospatial data, build scalable data pipelines, and enhance model performance for mineral exploration.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

Own Growth analytics end-to-end: build and maintain production data pipelines and dbt models, define north-star metrics and dashboards, design and run A/B experiments using causal inference, embed LLM/GenAI tooling, and translate insights into strategic recommendations for leadership.

Lead large-scale technical initiatives on the Data Ingestion Team, focusing on building and operating distributed systems that process billions of events daily.

Design, build, and maintain BI dashboards and reports; write advanced SQL to extract and validate data; recommend KPIs; manage reporting projects; partner with Product/Revenue/Operations; own BI reporting cycles and adopt AI/LLM tools to accelerate analysis and automation.

Design, develop, and optimize scalable data solutions and data pipelines using Databricks, Python, SQL, and Azure. Collaborate across teams for data integration and quality assurance.

Responsible for designing, building, and maintaining scalable data pipelines using Databricks. Optimize ETL/ELT processes and ensure data quality, governance, and security.

The Senior Data Scientist will develop models and analyses for risk and revenue decisions, collaborating with various teams to optimize funding for eCommerce.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

The Analytics Engineer will design data models, build pipelines, and ensure data quality to support AI evaluation and insights.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.