Senior Data & AI Productivity Analyst

Job Title: Senior Data & AI Productivity Analyst Job Type: T4 Contract Location: Remote - Toronto, Ontario, Canada Experience: 8+ Years Rate: CAD $67 - $74 per hour Education: Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative discipline. Role Summary NearSource is seeking a Senior Data & AI Productivity Analyst to help measure, evaluate, and scale the impact of AI-native and AI-augmented tools across enterprise platform organizations. This role will partner with product, engineering, strategy, and finance teams to establish trusted metrics, uncover actionable insights, and drive data-informed decisions that improve productivity, operational effectiveness, and product outcomes. The successful candidate will combine advanced analytics expertise with hands-on experience leveraging AI tools to accelerate analysis, experimentation, and decision-making. This role is ideal for a data professional who thrives at the intersection of analytics, AI innovation, business strategy, and platform transformation. Key Responsibilities Partner with product managers, engineering leaders, and cross-functional stakeholders to define business questions, success metrics, and analytical frameworks for AI tooling, platform productivity, and emerging technology initiatives. Analyze large and complex datasets to identify adoption patterns, usage behaviors, productivity trends, and opportunities to improve AI-enabled workflows and platform outcomes. Monitor and report on key performance indicators across AI initiatives, providing leadership teams with visibility into performance, risks, opportunities, and strategic impact. Consolidate and integrate data from multiple sources to create trusted, scalable analytics assets that support organizational decision-making. Develop clear, impactful dashboards, reports, and visualizations that communicate complex findings to both technical and non-technical stakeholders. Apply statistical analysis, forecasting, experimentation methodologies, and predictive modeling techniques to evaluate initiative effectiveness and guide prioritization decisions. Design and maintain scalable analytics data models, semantic layers, and governed datasets that enable reliable self-service reporting across the organization. Leverage AI tools and AI-assisted workflows to accelerate analysis, automate repetitive tasks, build lightweight prototypes, and enhance analytical productivity. Ensure data quality, consistency, and integrity through robust validation, monitoring, and governance practices. Translate analytical findings into actionable recommendations that influence product strategy, investment decisions, and operational improvements. Must-Have Skills 8+ years of experience in data analytics, business intelligence, product analytics, or a related field within a technology or SaaS environment. Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative discipline. Demonstrated experience using AI productivity tools such as Claude Code, Cursor, or similar platforms to extend analytical capabilities and automate workflows. Hands-on experience leveraging AI tooling to accelerate data analysis, generate insights, and develop lightweight analytical solutions or prototypes. Advanced SQL expertise for querying, transforming, and analyzing large-scale datasets. Strong proficiency in Python or R for data analysis, statistical modeling, automation, and experimentation. Experience working with modern data platforms and ELT technologies, including Snowflake, dbt, Airflow, or equivalent solutions. Experience designing and maintaining scalable analytics data models, semantic layers, and governed reporting datasets. Experience developing dashboards and executive reporting using Looker, Power BI, or comparable visualization platforms. Strong understanding of statistical analysis, experimentation frameworks, forecasting methodologies, and predictive analytics techniques. Experience working with cloud platforms such as AWS, Azure, or similar environments. Proven analytical, problem-solving, and critical-thinking capabilities. Strong ability to communicate complex data insights and recommendations to both technical and non-technical stakeholders. Proven ability to collaborate effectively across product, engineering, strategy, finance, and executive leadership teams. Nice-to-Have Skills Experience working within platform engineering, developer productivity, or internal tooling organizations. Prior experience measuring the impact and adoption of AI-enabled products, workflows, or productivity initiatives. Familiarity with product analytics frameworks, experimentation platforms, and usage telemetry analysis. Experience supporting strategic planning, investment analysis, or operational performance initiatives. Knowledge of enterprise SaaS business models and platform ecosystems. Familia