Data Scientist, Product Analytics Engineering

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Company Overview

A rapidly growing live commerce and marketplace platform is transforming how people buy, sell, and discover products online. The organization operates across numerous categories, connecting buyers and sellers while building technology that supports a rapidly expanding commerce ecosystem.

The company operates as a distributed, remote-friendly organization with teams across the United States, United Kingdom, Ireland, Poland, Germany, and Australia. Its culture emphasizes speed, customer focus, ownership, collaboration, and measurable impact.

The salary or hourly rate range may be inclusive of several levels applicable to the position. Final compensation will depend on factors including level, relevant prior experience, skills, and expertise. The stated range represents base salary or hourly rate and does not include benefits or equity.

The organization is seeking a Data Scientist, Product Analytics Engineering to help shape product strategy through data-driven insights, experimentation, and measurement. The role will partner closely with Product, Engineering, Design, and Operations teams to understand user behavior, improve product experiences, and support strategic decision-making across the organization.

Key Responsibilities

• Define and own KPIs that measure product health, user engagement, and marketplace performance.
• Analyze user behavior, product usage patterns, and marketplace dynamics to identify opportunities and inform product priorities.
• Translate complex datasets and analytical findings into actionable recommendations for product and leadership teams.
• Partner with product managers and engineers to design, implement, and evaluate A/B tests and feature rollouts.
• Develop frameworks for causal inference, impact measurement, and long-term product evaluation.
• Build scalable methodologies for evaluating feature performance and guiding product iteration.
• Use modern data technologies to build dashboards, data pipelines, and self-service tools.
• Partner with engineering teams to improve data accessibility and quality.
• Support instrumentation for new product features and ensure reliable measurement.
• Advocate for data-driven decision-making and foster a culture of measurement across the product organization.
• Communicate insights clearly and effectively to technical and non-technical audiences.
• Influence product roadmaps and strategic decisions through data and analytical insights.
• Serve as a strategic thought partner to product leaders in building, launching, and improving experiences across the platform.
• Lead cross-functional analytical projects with a high degree of ownership.

Required Qualifications

• 3+ years of experience in Data Science, Decision Science, or Analytics within a product-focused organization.
• Bachelor’s degree in Computer Science, Economics, Statistics, or another related quantitative field, or equivalent professional experience.
• Proven experience applying statistical and analytical methods to real-world product problems.
• Advanced SQL skills.
• Experience working with modern data warehouses such as Snowflake, BigQuery, or Redshift.
• Experience with data processing and analytics tools such as Spark or dbt.
• Proficiency in Python or R for data analysis, modeling, and experimentation.
• Experience designing and analyzing A/B tests.
• Understanding of causal inference techniques.
• Strong data visualization skills and experience with business intelligence tools.
• Ability to communicate complex analytical concepts clearly, concisely, and effectively.
• Experience leading cross-functional projects and influencing product strategy through data.
• Ability to work effectively in fast-paced and ambiguous environments with a high degree of ownership.
• Strong curiosity and a user-focused approach to product analytics.
• Ability to prioritize outcomes and business impact while collaborating effectively with cross-functional teams.

Work Arrangement

The role offers flexibility to work remotely or from designated office hubs. Team members based in the United States are expected to live within commuting distance of the organization’s hubs in New York, Seattle, Los Angeles, or San Francisco, with in-person collaboration encouraged for planning, problem-solving, and team connection.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
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