Data Scientist

🕒 September 24

🏄 California, New York, +1 more states – Remote

🏄 California – Remote 🗽 New York – Remote ☕ Washington – Remote

💵 $225k - $275k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Superhuman

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

☁️ SaaS

⚡ Productivity

🤖 Artificial Intelligence

SaaS • Productivity • Artificial Intelligence

Superhuman is a productivity software company that offers a suite of tools — Mail, Docs, Go (an AI assistant), Calendars, and Databases — 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.

📋 Description

• Act as the embedded data science partner for the Mail core product team • Shape feature strategy, prioritization, and roadmap decisions using evidence • Define and own metrics for activation, engagement, retention, and feature impact • 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 that predict conversion and churn • Use behavioral insights to improve onboarding, feature discovery, and engagement nudges • Analyze how Calendar scheduling and MCP-driven workflows affect daily Mail usage • Communicate experiment readouts and strategic findings to product managers, designers, engineers, and executives • Partner with product managers, engineers, designers, ML engineers, and the Experimentation team running on Statsig

🎯 Requirements

• 5+ years of data science experience • 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 communicate technical insights clearly • Bachelor’s degree in a quantitative field such as statistics, mathematics, economics, computer science, or data science • Experience working at a fast-growing startup, on AI-native consumer products, and/or in B2B/SaaS is nice to have • Experience as a strategic thought partner to product, growth, or business leaders is nice to have • Hands-on evaluation of AI, LLM, or agentic products is nice to have • Familiarity with AI-assisted development tools such as Claude Code or Codex is nice to have • Familiarity with experimentation platforms such as Statsig and modern data stacks such as Databricks is nice to have • Experience with product-led growth and/or lifecycle and marketing analytics is nice to have • Experience establishing data science team methods, standards, and processes is nice to have

🏖️ Benefits

• 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 work model • Hybrid setup available for those based in San Francisco, New York City, or Seattle

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