Apply for the Senior Product Data Scientist

Summary

We're looking for a Product Data Scientist who is deeply focused on understanding user behavior and driving product decision-making through experimentation. This person will work closely with product managers, engineers, and design to identify opportunities, run structured A/B tests, and uncover insights that directly influence the product roadmap. The ideal candidate is comfortable owning experiments end-to-end — from hypothesis to rollout — and translating complex data into clear direction for the product team.

Key Responsibilities

Analyze user behavior patterns, product usage flows, drop-offs, and engagement trends.
Design, execute, and evaluate A/B tests and other experimentation frameworks to validate product decisions.
Partner with product teams to define key metrics, success criteria, and hypotheses for upcoming features.
Build dashboards and self-serve tools that help the product team understand the health of the product.
Work with data engineers to ensure clean, reliable, and accessible data for analysis.
Translate complex findings into clear, actionable insights for stakeholders.

Core Requirements

Strong experience with A/B testing, experiment design, hypothesis testing, and interpreting experiment results.
Solid skills in SQL and Python for data manipulation and analysis.
Experience working with data warehousing and workflow tools (Snowflake, Airflow, Superset, Eppo, etc.).
Background in product analytics or product-facing data science roles.
Ability to communicate insights clearly and influence product strategy using data.
Excellent written and verbal communication skills in English.
Ability to work independently in a remote, fast-paced environment.

Additional

Latin America Timezone Overlap: 7h of daily overlap with GMT-3 required.

Apply for the Senior Product Data Scientist

Summary

Key Responsibilities

Analyze user behavior patterns, product usage flows, drop-offs, and engagement trends.
Design, execute, and evaluate A/B tests and other experimentation frameworks to validate product decisions.
Partner with product teams to define key metrics, success criteria, and hypotheses for upcoming features.
Build dashboards and self-serve tools that help the product team understand the health of the product.
Work with data engineers to ensure clean, reliable, and accessible data for analysis.
Translate complex findings into clear, actionable insights for stakeholders.

Core Requirements

Strong experience with A/B testing, experiment design, hypothesis testing, and interpreting experiment results.
Solid skills in SQL and Python for data manipulation and analysis.
Experience working with data warehousing and workflow tools (Snowflake, Airflow, Superset, Eppo, etc.).
Background in product analytics or product-facing data science roles.
Ability to communicate insights clearly and influence product strategy using data.
Excellent written and verbal communication skills in English.
Ability to work independently in a remote, fast-paced environment.

Additional

Latin America Timezone Overlap: 7h of daily overlap with GMT-3 required.