Description

Product Analyst
As a Product Analyst, you will drive data-informed product decisions by delivering actionable insights, designing robust experiments, and developing a deep understanding of user behavior. You will partner closely with Product, UX, and Engineering teams to shape product strategy and enhance the customer experience across security products.

Key Responsibilities
Experimentation Strategy: Design, execute, and analyze A/B tests and quasi-experiments to evaluate the impact of products and features on engagement, retention, and customer satisfaction.
Product Insights: Conduct deep-dive analyses of user journeys, onboarding funnels, feature adoption, and retention cohorts to identify growth and optimization opportunities.
Metrics and Measurement: Establish north-star metrics, KPIs, and guardrails, and ensure consistent definitions across teams and dashboards.
Decision Support: Translate complex analyses into clear, actionable recommendations that inform product roadmaps and prioritization.
Data Foundations: Partner with data engineering and platform teams to ensure high-quality telemetry, scalable data models, and reliable reporting layers.
Advanced Analytics: Apply statistical techniques—including segmentation, cohort analysis, regression, and causal inference—to uncover the drivers of user behavior and product performance.
Cross-Functional Collaboration: Work closely with Product Managers, Designers, and Engineers to embed analytics throughout the product development lifecycle.
Analytics Leadership: Mentor analysts and elevate team practices in experiment design, metric definition, and data storytelling.
Stakeholder Communication: Present clear, compelling insights to stakeholders and leadership through dashboards, presentations, and data-driven narratives.

Qualifications
Experience: 5–8 years of experience in product analytics, advanced analytics, or data science, with a strong product focus.
Experimentation: Hands-on experience designing and interpreting A/B tests and quasi-experimental methods, such as difference-in-differences and matching.
Analytical Skills: Proficiency in SQL and Python for data analysis, supported by a strong foundation in statistics and hypothesis testing.
Product Analytics: Deep understanding of user behavior analysis, funnel optimization, retention, and feature-adoption metrics.
Data Visualization and Storytelling: Experience using BI tools such as Power BI, Tableau, or Looker to communicate insights effectively.
Telemetry and Data Modeling: Experience working with event-based data and defining tracking requirements for digital products.
Business and Product Acumen: Ability to connect data insights with product strategy and customer experience improvements.
Communication and Stakeholder Management: Strong communication and stakeholder management skills, with the ability to influence decisions across teams.

Education: Bachelor’s or master’s degree in a quantitative field—such as Statistics, Computer Science, Engineering, Mathematics, or a related discipline—is preferred

Key Skills

Education

Any Graduate