Data Scientist, Mail (US)

Superhuman; United States; Remote; USD 140,000 - 195,000; Full time

Job summary

Superhuman is seeking a Data Scientist on the Mail team to embed with product, design and engineering. You’ll shape feature strategy, define success metrics, and run experiments to improve activation, engagement, retention, and expansion.

You’ll build measurement frameworks for AI features like Auto Drafts, Auto Labels, and Calendar, influence cross‑functional decision making, and help the company ship faster while delivering delightful, data‑driven user experiences.

Responsibilities

• Be the embedded data science partner for the Mail core product team, shaping strategy and roadmap with evidence.
• Define and own the metrics that matter for Mail: activation milestones, engagement depth, retention curves, and leading indicators.
• Design and run experiments across the Mail product lifecycle and build measurement frameworks to separate signal from noise.
• Shape measurement for Mail AI features (Auto Drafts, Auto Labels, Auto Archive, Calendar, MCP) with quality metrics.
• Figure out what makes Mail sticky: engagement drivers, activation sequence for power users, funnel value leakage.
• Partner with product-led and sales-led growth to quantify levers turning users into team expansions and signal conversion/churn.
• Use data to craft product moments — onboarding flows, feature discovery, engagement nudges that feel natural.
• This includes understanding how features such as Calendar scheduling and MCP-driven workflows change day-to-day Mail usage.
• Communicate findings clearly to PMs, designers, engineers, and executives — experiment readouts and strategic deep-dives — raise the bar on data-driven decisions.

Job description

Superhuman offers a remote-flexible working model for this particular role on the Mail team. This gives team members plenty of focus time and the flexibility to do their best work from wherever they’re based, while staying closely connected to a collaborative, tight-knit team culture. For those based in San Francisco, New York City, or Seattle, a hybrid setup is also available.

About Superhuman

Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company’s products include Grammarly’s writing assistance, Docs’ collaborative workspace, Mail’s inbox management, and Go, the proactive AI assistant that understands context and automatically delivers help. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at superhuman.com and about our values here.

The Opportunity

Want to use data science to shape how one of the most beloved productivity products in the world grows, retains, and delights its users? This Data Scientist position is embedded in the Superhuman Mail business unit, working alongside Data Engineering, Finance, RevOps, and UX Market Research. Together, you act as one numbers-and-insights team, with a direct line to the leaders setting strategy and a shared mandate to move the metrics that matter.

Superhuman Mail is the fastest, most AI-native email experience ever built. It helps knowledge workers and teams fly through their inbox twice as fast, stay on top of what matters most, and collaborate without friction — saving users four hours every single week. Where email has barely changed in decades, Superhuman Mail is reimagining it from the ground up: AI that drafts replies in your voice, auto-labels and triages incoming messages, surfaces follow-ups before you drop the ball, and can even send emails on your behalf. It serves everyone, from individual professionals to Fortune 500 sales teams, and boasts a deeply loyal user base and a product people genuinely love. The data environment is rich, the growth questions are hard, and the opportunity to drive real impact — on acquisition, activation, retention, and expansion — is enormous.

Your work on Mail is part of a broader platform story. The Superhuman Platform suite includes Grammarly’s writing assistance, Mail, Docs, Databases, and Go, our proactive AI assistant. As a compound startup, we’re building an integrated suite rather than separate tools — so insights you surface in Mail ripple across the full product portfolio, and cross-product growth loops connect the dots between how users discover, adopt, and expand across the suite. Our products serve both consumers and enterprises, creating an unusually rich data environment. Our user base spans students and knowledge workers, individual users and Fortune 500 companies, universities and global enterprises, across a growing range of languages and markets. That breadth creates no shortage of important questions to own.

This is an opportunity for those drawn to complex, high-stakes growth problems — in a product people are passionate about — who want their work to measurably change outcomes.

What you’ll do

• Be the embedded data science partner for the Mail core product team — shaping feature strategy, prioritization, and roadmap decisions with evidence, not just fielding ad hoc requests.
• Define and own the metrics that matter for Mail: activation milestones, engagement depth, retention curves, and the leading indicators that tell us whether a new feature is actually changing how people work in their inbox.
• Design and run experiments across the Mail product lifecycle — from onboarding and first-week activation to long-term habit formation — and build the measurement frameworks that separate signal from noise.
• Shape the measurement strategy for Mail’s AI features — Auto Drafts, Auto Labels, Auto Archive, Calendar, MCP, and the agentic capabilities on the roadmap — by defining quality frameworks and behavioral metrics that show whether AI is making users genuinely faster and more effective.
• Figure out what makes Mail sticky: which features drive the deepest engagement, what the activation sequence looks like for users who become power users, and where in the funnel we’re leaving value on the table.
• Partner with product-led and sales-led growth to identify and quantify the levers that turn individual users into team expansions — and surface the product signals that predict conversion and churn.
• Use data to craft remarkable product moments — turning behavioral insight into smarter onboarding flows, better feature discovery, and engagement nudges that feel natural rather than forced. This includes understanding how features such as Calendar scheduling and MCP-driven workflows change the way users interact with Mail on a day-to-day basis.
• Communicate findings clearly to PMs, designers, engineers, and executives — from experiment readouts to strategic deep-dives — and help raise the bar on how the Mail team makes decisions with data.