Principal Product Data Scientist

This job was selected by the SpringCube team to help AI, Data and Cloud Engineers discover relevant San Francisco Bay Area employers. Sign up to view the full employer details and apply directly with the hiring company.

Company Overview

A leading collaboration and workplace technology platform provides tools that help organizations communicate, collaborate, and make data-driven decisions. The organization fosters a positive, diverse, and supportive culture and values curiosity, continuous improvement, collaboration, and innovation.

The organization is building a world-class data ecosystem designed to support and scale data-driven product decision-making. Its data teams work closely with Product, Design, Engineering, and Go-to-Market functions to translate data into actionable insights and influence product strategy.

The organization is seeking Staff / Principal Product Data Scientists to help shape product development, define success metrics, evaluate product opportunities, and build scalable data capabilities. This role will work closely with cross-functional partners to identify opportunities, derive insights, and influence decisions about what products and features to build and how their success is measured.

The role will also contribute to the design and development of an agentic data delivery platform. By connecting data infrastructure, metrics foundations, and analytical insights, the team aims to expand self-service access to data within AI and agentic environments.

Key Responsibilities

• Establish strong partnerships with product stakeholders to identify opportunities, prioritize roadmaps, and support execution excellence.
• Promote evidence-based decision-making by partnering with key leaders and improving accessibility to data and insights.
• Evaluate the key factors that influence adoption of product capabilities using quantitative and evidence-based analysis.
• Develop success metric frameworks and self-service reporting to monitor product health.
• Prototype foundational data models and collaborate with Data Engineering teams to develop canonical sources of truth.
• Contribute to the design and implementation of an agentic data delivery platform.
• Use quantitative analysis to identify product opportunities that can improve user experiences and create business value.
• Partner closely with Product Researchers to align roadmaps and collaborate on projects addressing complex product and business questions.
• Work with Product, Design, Engineering, and Go-to-Market teams to influence product development and strategic decisions.
• Translate complex analytical findings into clear recommendations and insights for executive and cross-functional audiences.
• Help establish scalable data practices that enable self-service analytics and data-driven product decision-making.

Required Qualifications

• 5+ years of experience in product data science or a related field within the technology industry.
• Demonstrated experience using data to influence product teams and support ambitious business and product objectives.
• Advanced proficiency in SQL.
• Proficiency in at least one programming language used for data science, such as Python, R, or Scala.
• Strong foundation in statistics, experimentation, causal inference, machine learning, and analytical problem-solving.
• Experience working with large-scale data technologies such as Spark, Presto, Hive, Hadoop, or comparable distributed data platforms.
• Ability to communicate complex analytical findings clearly to executive and cross-functional audiences.
• Strong ability to collaborate with Product, Design, Engineering, Research, and other cross-functional teams.
• Experience applying quantitative analysis to product strategy and decision-making.
• A related degree is required.

Preferred Qualifications

• Bachelor’s degree in a quantitative field such as Computer Science, Economics, Physics, or a related discipline.
• Advanced degree such as a Master’s or PhD is a strong plus.
• Knowledge of workflow orchestration tools such as Apache Airflow.
• Experience developing data models and metrics foundations for large-scale product organizations.
• Experience working with AI, agentic systems, or self-service data platforms.
• Strong ability to operate in collaborative, fast-paced, and evolving technical environments.

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.

3.To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.

4.No Liability: SpringCube is not liable for inaccuracies.