Product Data Analyst
$150,000–$200,000 year
HybridMontréal, Quebec, Canada
Job Summary
Partner with the Product team to explore problem areas, uncover behavioral trends, and use data to influence the product roadmap. Conduct deep-dive data analyses to guide strategic decision-making, uncover growth opportunities, and translate insights into action. Collaborate with development teams to design, integrate, and maintain robust analytics tracking, telemetry, and event pipelines across platforms. Integrate modern AI tools into daily analysis to focus on problem definition, stakeholder alignment, and insight translation rather than manual tasks. This role serves as the engine for product decisions, shaping strategy and measuring performance within Dialogue's Integrated Health PlatformMD. The position requires 5+ years of experience, deep SQL proficiency, and familiarity with Snowflake, Metabase, and dbt. Candidates must thrive in a fast-moving, high-autonomy environment with 3 days/week hybrid work in Montreal or Toronto.
Required Qualifications
- 5+ years of experience in a Product Analyst, Data Analyst, or Business Intelligence role within a fast-paced environment
- Deep proficiency with SQL
- Hands-on experience or familiarity with our tech stack (Snowflake, Metabase, dbt, Evidence)
- Exceptional ability to synthesize complex data points into clear, executive-level stories and strategic recommendations
- Comfort using AI tools (e.g., LLM-assisted SQL/Python coding, automated data analysis) combined with the critical judgment to stress-test outputs, question assumptions, and validate analytical results at scale
- Experience working within vertically integrated product teams (Data + Product + Development) with a proactive, high-integrity approach to problem-solving
- Ability to thrive in a fast-moving, high-autonomy environment where you define problems as much as you solve them
- Strong hands-on experience designing and analyzing A/B tests (hypothesis testing, sample size calculation, statistical significance, and contextual interpretation)
Desired Qualifications
- Experience working with large-scale event streams and/or conversational data
- Applied knowledge of advanced product analytics frameworks (e.g., time-series/survival analysis, cohort and retention modeling, or basic causal inference)
- Prior experience working with sensitive data (PI/PHI) in data pipelines and skills/experience with anonymization techniques
- Familiar with dimensional modelling concepts
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