AI Productivity Data Analyst

Hybrid Role, 40 hours per week in EST. Toronto area preferred. We are seeking a highly analytical and strategic AI Productivity Analyst to help measure, evaluate, and optimize the impact of AI-powered tools and productivity initiatives across the organization. As we continue to expand the adoption of AI-native and AI-augmented solutions, this role will play a critical part in defining success metrics, uncovering actionable insights, and guiding data-driven investment decisions. The ideal candidate combines deep expertise in data analytics, business intelligence, and statistical modeling with hands-on experience leveraging modern AI tools such as Claude, Cursor, and other AI-assisted technologies. You will work closely with Product, Engineering, Strategy, and Finance leaders to evaluate AI adoption, measure business outcomes, and influence the future direction of AI-enabled initiatives.. Requirements: • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or another quantitative discipline. • 8+ years of experience in Data Analytics, Business Intelligence, Data Science, or a related analytical field within technology, SaaS, or platform-based organizations. • Experience using AI-powered tools (e.g., Claude, Cursor, GitHub Copilot, or similar) to enhance productivity, automate workflows, and accelerate analytical work. • Strong expertise in SQL and proficiency in Python and/or R for advanced analytics, modeling, and data manipulation. • Hands-on experience with modern data platforms and ELT technologies such as Snowflake, dbt, Airflow, or equivalent solutions. • Experience designing scalable analytics data models and supporting self-service reporting environments. • Advanced experience with BI and data visualization tools such as Power BI, Looker, Tableau, or similar platforms. • Strong understanding of statistical analysis, experimentation, forecasting, and predictive modeling techniques. • Exceptional problem-solving skills with the ability to independently analyze complex datasets and generate actionable insights. • Excellent communication and stakeholder management skills, with the ability to present findings effectively to technical and executive audiences. Responsibilities: • Partner with Product Managers, Engineering Leaders, Strategy, and Finance teams to define business questions, success metrics, and analytical frameworks for AI-driven initiatives. • Analyze large, complex datasets to identify trends, adoption patterns, productivity gains, and opportunities for optimization. • Develop and monitor KPIs that measure the effectiveness of AI tooling, platform initiatives, and operational performance. • Evaluate how internal teams and customers interact with AI-enabled capabilities, identifying friction points and areas for improvement. • Design and maintain scalable analytics data models, governed datasets, and semantic layers that support trusted business reporting and decision-making. • Build compelling dashboards, reports, and visualizations using tools such as Looker, Power BI, or similar platforms. • Apply statistical analysis, experimentation methodologies, forecasting techniques, and predictive modeling to assess initiative impact and support strategic prioritization. • Ensure data integrity, quality, and consistency through robust data governance and validation practices. • Translate complex analytical findings into clear, actionable recommendations for both technical and non-technical stakeholders. • Support executive and leadership teams with data-driven insights that influence product strategy, operational decisions, and future AI investments. Preferred Qualifications: • Previous experience working within a SaaS, platform engineering, or cloud technology environment. • Familiarity with AI adoption measurement, productivity analytics, and technology investment analysis. • Experience working with cloud platforms such as AWS, Azure, or Google Cloud. • Knowledge of products an