Data Scientist, Mail

This is a fully remote position, open to applicants in United States.

📋 Description

• Act as the integrated data science collaborator for the Mail core product team.

• Influence feature strategy, prioritization, and roadmap decisions through data-driven evidence.

• Establish and manage Mail metrics, encompassing activation, engagement, retention, and feature-impact indicators.

• Develop and execute experiments focused on onboarding, activation, and the formation of long-term habits.

• Create measurement frameworks that distinguish signal from noise.

• Formulate measurement strategies for Mail AI features such as Auto Drafts, Auto Labels, Auto Archive, Calendar, MCP, and agentic capabilities.

• Establish quality frameworks and behavioral metrics for AI functionalities.

• Evaluate feature engagement, activation sequences, power-user behaviors, and identify funnel opportunities.

• Recognize and assess factors that convert individual users into team expansions.

• Highlight product signals that forecast conversion and churn.

• Leverage behavioral insights to enhance onboarding, feature discovery, and engagement prompts.

• Examine the impact of Calendar scheduling and MCP-driven workflows on user behavior.

• Present findings to product managers, designers, engineers, and executives through experiment summaries and strategic analyses.

• Collaborate with product managers, engineers, designers, ML engineers, and the Experimentation team utilizing Statsig.

⛳️ Requirements

• Over 5 years of experience in data science.

• Proven history of generating measurable impacts for both business and customers.

• Extensive knowledge in experimentation and causal inference.

• Proficient in A/B testing, quasi-experimental techniques, and observational methodologies.

• Expertise in Python and SQL.

• Strong skills in data exploration and manipulation.

• Solid foundation in applied statistics and machine learning.

• Capability to convert ambiguous business inquiries into experimental designs, measurement strategies, and metrics.

• Ability to influence cross-functional partners and translate technical insights into actionable steps through effective communication.

• Self-motivated, creative problem-solver, and capable of thriving in ambiguous situations.

• Bachelor’s degree in a quantitative discipline such as statistics, mathematics, economics, computer science, or data science.

• Advanced degree or equivalent practical experience is preferred.

• Nice to have: experience at a rapidly growing startup, AI-native consumer products, and/or B2B/SaaS.

• Nice to have: strategic collaboration with product, growth, or business leaders.

• Nice to have: hands-on experience evaluating AI, LLM, or agentic products.

• Nice to have: familiarity with AI-assisted development tools like Claude Code or Codex.

• Nice to have: experience with experimentation platforms like Statsig and modern data stacks such as Databricks.

• Nice to have: experience in product-led growth, lifecycle, and marketing analytics.

• Nice to have: experience in establishing methods, standards, and processes for data science teams.

🏝️ Benefits

• Comprehensive health care benefits, including medical, dental, vision, mental health, and fertility support.

• Options for disability and life insurance.

• 401(k) matching program.

• Paid parental leave.

• 20 days of paid time off annually.

• 12 paid holidays per year.

• Two floating holidays each year.

• Flexible sick leave policy.

• Caregiving stipend.

• Pet care stipend.

• Wellness stipend.

• Home office stipend.

• Annual budget for professional development.

• Opportunities for professional growth.

• Flexible remote working model.

• Hybrid work arrangement available for employees located in San Francisco, New York City, or Seattle.