Were looking for a curious and proactive Product Analyst with strong analytical and technical skills. Someone who loves digging into user-level data, analyzing funnels and experiments, and turning insights into product improvements. The ideal candidate has an appetite for problem-solving, collaborates closely with product managers and developers, and influences decision-making with data-driven recommendations.
We move quickly, were agile and dynamic, and we work in a fun and challenging environment.
In this position, you will:
Partner closely with product managers, designers, and developers to evaluate product performance and guide decisions with data.
Design, run, and analyze A/B tests and experiments to measure impact on user behavior.
Analyze user-level funnels and journeys to uncover friction points and opportunities for growth.
Build and maintain informative, actionable dashboards and reports for monitoring product KPIs and enabling self-serve analytics.
Provide methodologies and frameworks to accurately measure product performance, feature adoption, and long-term user retention.
Write advanced SQL queries and leverage Python or statistical tools for deep-dive analyses.
Proactively surface insights and hypotheses that can inspire new product initiatives.
Requirements: Requirements:
4+ years of experience as an analyst in a tech company.
Strong expertise in SQL and experience with data warehouses and cloud systems.
Hands-on experience with A/B testing methodologies and funnel analysis.
Knowledge of Python for data preparation, statistical testing, and modeling.
Strong analytical and statistical skills with a hypothesis-driven mindset.
Experience with BI tools (Looker, Tableau, or BI-as-code tools).
Excellent communication and collaboration skills, with the ability to translate data into actionable insights for both technical and non-technical teams.
Curiosity, problem-solving appetite, and ability to thrive in a fast-paced, dynamic startup environment.
Exposure to automation of analytics tasks with AI tools.
Nice-to-have:
Experience in e-commerce, travel, or other high-volume consumer products.
Background in Data Modeling, Information Systems, or Computer Science.
This position is open to all candidates.