Drive data-informed product decisions through experimentation, cohort and funnel analyses, metric definition, and telemetry modeling. Partner with Product, UX, and Engineering to improve engagement, retention, and customer experience; translate analyses into actionable roadmap recommendations and mentor analytics practices.
As a Product Analyst you will drive data informed product
decisions by delivering actionable insights designing robust experiments and
deeply understanding user behaviour You will partner closely with Product UX
and Engineering to shape product strategy and improve customer experience
across the security products
Key Responsibilities
- Lead experimentation strategy Design execute and analyze AB
tests and quasi experiments to evaluate product and feature impact on
engagement retention and customer satisfaction
- Drive product insights Conduct deep dive analyses on user
journeys onboarding funnels feature adoption and retention cohorts to identify
growth and optimization opportunities
- Define and operationalize metrics Establish northstar
metrics KPIs and guardrails ensure consistent definitions across teams and
dashboards
- Enable product decision making Translate complex analyses
into clear actionable recommendations for product roadmaps and prioritization
- Improve data foundations Partner with data engineering and
platform teams to ensure high-quality telemetry scalable data models and
reliable reporting layers
- Leverage advanced analytics Apply statistical techniques
segmentation cohort analysis regression causal inference to uncover drivers of
user behavior and product performance
- Collaborate cross functionally Work closely with Product
Managers Designers and Engineers to embed analytics into the product
development lifecycle
- Mentor and elevate analytics practices Guide analysts on
experimentation design metric definition and storytelling best practices
- Communicate effectively Deliver clear compelling insights to
stakeholders and leadership through dashboards presentations and narratives
Requirements
- 5-8 years of experience in product analytics advanced
analytics or data science with strong product focus
- Strong experimentation expertise Handson experience
designing and interpreting AB tests and quasi experimental methods e.g.
difference indifferences matching
- Advanced analytical skills Proficient in SQL and Python for
data analysis strong foundation in statistics and hypothesis testing
- Product analytics experience Deep understanding of user
behavior analysis funnel optimization retention and feature adoption metrics
- Data visualization storytelling Experience with BI tools
such as Power BI Tableau or Looker to communicate insights effectively
- Telemetry data modelling knowledge Experience working with event-based
data and defining tracking for digital products
- Business and product acumen Ability to connect data insights
into product strategy and customer experience improvements
- Strong communication and stakeholder management skills with
the ability to influence decisions across teams
- Bachelor’s or master’s degree in a quantitative field a plus
Statistics Computer Science Engineering Mathematics or related
Skills
- Mandatory Skills: ANSI-SQL, Python for DATA
Similar Jobs
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Business Intelligence
Support the Financial Data product by translating roadmap goals into engineering requirements, creating mockups and business logic, querying PostgreSQL/Snowflake/Athena for data insights, performing data validation and QA, documenting product features, coordinating cross-team prioritization, and contributing to release communications.
Top Skills:
Amazon AthenaPostgresPythonSnowflakeSQL
Insurance
Analyze and document underwriting workflows, collaborate with Product Owners and SMEs to design optimized AI-driven underwriting solutions, translate business needs into actionable requirements, manage change and UAT, evaluate product outcomes, and support solutions from inception through deployment to ensure business value.
Insurance
Lead integration and product quality assurance for AI-driven P&C underwriting solutions. Translate underwriting business needs into clear requirements, coordinate cross-functional teams, drive issue resolution, support lifecycle from inception to deployment, and recommend workflow optimizations using underwriting expertise.
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.
