Senior Product Analyst

Role overview

This is a senior analytics role for a Canada-based professional who will partner with product, design, and engineering to turn product usage data into decisions that improve the roadmap, customer experience, and business performance. The opportunity sits within a remote-first technology environment and carries a high level of ownership, autonomy, and visibility.

The position is posted on behalf of a partner organization, which will handle applications and the rest of the hiring process. The role is designed for someone who enjoys connecting customer behavior with product improvements and helping shape a strong data-driven culture.

What you will do

• Act as the main analytics partner for product, design, and engineering teams, owning the product analytics function end to end.
• Create and oversee tracking plans, event naming structures, instrumentation standards, and broader analytics frameworks.
• Study customer behavior, product usage, adoption, retention, engagement patterns, and user journeys to surface practical insights.
• Plan, run, and review A/B tests and other product experiments with sound measurement methods and clear success criteria.
• Develop and upkeep dashboards, reports, and other analytical resources that track key product performance indicators.
• Work with data engineering to make sure product data is reliable, scalable, and easy for teams to access.
• Convert product and business questions into structured analysis and communicate the findings as clear recommendations.
• Document metric definitions, event standards, and analytics best practices so teams stay aligned.
• Use data to guide product strategy, roadmap choices, and ongoing performance monitoring.

What we are looking for

• At least 3–5+ years of experience in product analytics, product data science, or a closely related analytics role in a SaaS setting.
• Advanced SQL capability, including analysis of large event-based, behavioral, and time-series data sets.
• Practical experience with product analytics tools such as Mixpanel, including tracking design, funnels, cohort analysis, retention, and instrumentation.
• Solid grasp of experimentation methods, including A/B testing, statistical significance, sample sizing, and outcome measurement.
• Ability to turn complex data into strategic recommendations that influence product direction.
• Experience working with cross-functional partners such as product managers, engineers, designers, and senior leaders.
• Strong presentation and communication skills for both technical and non-technical audiences.
• Comfort working independently in a highly autonomous, remote-first setup.
• Exposure to BigQuery, dbt, notebook-based BI tools, feature flagging tools, or Python for deeper analysis is an added advantage.
• Background in B2B SaaS, customer support technology, or product-led growth environments is helpful.

Benefits and compensation

• Estimated annual pay of about CAD 125,000 to CAD 130,000, with equity opportunities.
• Fully remote arrangement with flexibility to work from anywhere in Canada.
• Flexible paid time off for vacations and personal time.
• Health insurance coverage for employees and eligible dependents.
• Fully paid parental leave, including support for adoption and foster care.
• Home office stipend to support a productive remote setup.
• Monthly coworking allowance for those who prefer an external workspace.
• Annual budget for professional development, certifications, conferences, and learning.
• A collaborative environment that values ownership, quality, innovation, and continuous improvement.
• Strong emphasis on balance, independence, and long-term career growth.

Application and hiring process

This role is managed by the hiring partner, who will review applications and handle the next steps directly. Applications are screened through an AI-assisted matching process that compares candidates against the core requirements and then shares a shortlist with the employer. Final interviews, assessments, and hiring decisions are made by the employer’s internal team.

Privacy and data handling

By submitting an application, candidates acknowledge that personal data may be processed to assess candidacy and shared with the hiring employer. This processing is described as being based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. Applicants may request access, correction, deletion, or objection to their data at any time.

Artificial intelligence tools may also be used to support parts of the recruitment workflow, such as reviewing applications, analyzing resumes, and identifying possible inconsistencies or verification signals in application materials. These tools assist the recruitment team but do not replace human judgment, and final hiring decisions remain with people.