
1001 - 5000 employees
âď¸ SaaS
⥠Productivity
đ¤ Artificial Intelligence
SaaS ⢠Productivity ⢠Artificial Intelligence
Superhuman is a productivity software company that offers a suite of tools â Mail, Docs, Go (an AI assistant), Calendars, and Databases â designed to make email and work across apps faster and more efficient. Its flagship product, Superhuman Mail, promotes faster inbox management, timely follow-ups, and saves users time; the platform integrates AI features (including writing assistance via Grammarly and AI agents like Go) and connects to many third-party apps (Gmail, Drive, Jira, Claude, ChatGPT, Cursor). Superhuman targets teams and enterprises with collaborative documents, knowledge management, workflows, and proactive AI that schedules meetings and helps across apps. The company markets to teams (marketing, IT, education, enterprises) and emphasizes AI-native collaboration, integrations, and productivity gains.
đĽ 2 minutes ago
đşđ¸ United States â Remote
đľ $202k - $275k / year
â° Full Time
đĄ Mid-level
đ Senior
đ Data Scientist
đť Ghost score 0%
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1001 - 5000 employees
âď¸ SaaS
⥠Productivity
đ¤ Artificial Intelligence
SaaS ⢠Productivity ⢠Artificial Intelligence
Superhuman is a productivity software company that offers a suite of tools â Mail, Docs, Go (an AI assistant), Calendars, and Databases â designed to make email and work across apps faster and more efficient. Its flagship product, Superhuman Mail, promotes faster inbox management, timely follow-ups, and saves users time; the platform integrates AI features (including writing assistance via Grammarly and AI agents like Go) and connects to many third-party apps (Gmail, Drive, Jira, Claude, ChatGPT, Cursor). Superhuman targets teams and enterprises with collaborative documents, knowledge management, workflows, and proactive AI that schedules meetings and helps across apps. The company markets to teams (marketing, IT, education, enterprises) and emphasizes AI-native collaboration, integrations, and productivity gains.
⢠Serve as the embedded data science partner for the Mail core product team ⢠Shape feature strategy, prioritization, and roadmap decisions using evidence ⢠Define and own Mail metrics, including activation, engagement, retention, and feature-impact indicators ⢠Design and run experiments across onboarding, activation, and long-term habit formation ⢠Build measurement frameworks that separate signal from noise ⢠Shape measurement strategy for Mail AI features including Auto Drafts, Auto Labels, Auto Archive, Calendar, MCP, and agentic capabilities ⢠Define quality frameworks and behavioral metrics for AI features ⢠Analyze feature engagement, activation sequences, power-user behavior, and funnel opportunities ⢠Identify and quantify levers that turn individual users into team expansions ⢠Surface product signals predicting conversion and churn ⢠Use behavioral insights to improve onboarding, feature discovery, and engagement nudges ⢠Analyze how Calendar scheduling and MCP-driven workflows affect user behavior ⢠Communicate findings to product managers, designers, engineers, and executives through experiment readouts and strategic deep-dives ⢠Collaborate with product managers, engineers, designers, ML engineers, and the Experimentation team using Statsig
⢠5+ years of data science experience ⢠Track record of driving measurable impact for business and customers ⢠Deep expertise in experimentation and causal inference ⢠Fluency in A/B testing, quasi-experimental methods, and observational methods ⢠Fluency in Python and SQL ⢠Strong data exploration and manipulation skills ⢠Strong applied statistics and machine learning skills ⢠Ability to translate ambiguous business questions into experimental designs, measurement plans, and metrics ⢠Ability to influence cross-functional partners and turn technical insight into action through clear communication ⢠Self-starting, creative problem-solving, and ability to thrive with ambiguity ⢠Bachelor's degree in a quantitative field such as statistics, mathematics, economics, computer science, or data science ⢠Advanced degree or equivalent practical experience preferred ⢠Nice to have: experience at a fast-growing startup, AI-native consumer products, and/or B2B/SaaS ⢠Nice to have: strategic partnership with product, growth, or business leaders ⢠Nice to have: hands-on evaluation of AI, LLM, or agentic products ⢠Nice to have: familiarity with AI-assisted development tools such as Claude Code or Codex ⢠Nice to have: familiarity with experimentation platforms such as Statsig and modern data stacks such as Databricks ⢠Nice to have: product-led growth and/or lifecycle and marketing analytics experience ⢠Nice to have: experience establishing data science team methods, standards, and processes
⢠Excellent health care, including medical, dental, vision, mental health, and fertility benefits ⢠Disability and life insurance options ⢠401(k) matching ⢠Paid parental leave ⢠20 days of paid time off per year ⢠12 days of paid holidays per year ⢠Two floating holidays per year ⢠Flexible sick time ⢠Caregiving stipend ⢠Pet care stipend ⢠Wellness stipend ⢠Home office stipend ⢠Annual professional development budget ⢠Professional development opportunities ⢠Remote-flexible working model ⢠Hybrid setup available for those based in San Francisco, New York City, or Seattle
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