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Superhuman

Data Scientist, Acquisition

Posted An Hour Ago
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Hybrid
Seattle, WA
180K-275K Annually
Senior level
Hybrid
Seattle, WA
180K-275K Annually
Senior level
Analyze acquisition data and guide marketing strategy, budget allocation, channel optimization, and growth decisions. Design incrementality experiments, develop marketing mix and allocation models, define acquisition metrics, identify new growth opportunities, and improve web conversion. Partner with Marketing, Engineering, Finance, Design, and User Research to translate statistical and machine learning insights into measurable business outcomes across paid, organic, consumer, and enterprise channels.
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Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.

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 delivers help automatically. 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

Turn complex data into growth decisions that shape the future of Superhuman’s product suite.

As an Acquisition Data Scientist at Superhuman, you’ll shape how we acquire, activate, and expand our user base across a diverse portfolio of consumer and enterprise products. You’ll partner directly with Acquisition Marketing to improve the effectiveness of paid and organic channels, optimize the web funnel, and ensure every marketing dollar drives measurable growth.

Your work will span the Superhuman product suite, including Grammarly, Mail, Docs, Databases, GPTZero, Fathom, and Go. Because we’re building an integrated platform rather than a collection of standalone tools, insights from one product can unlock growth across the portfolio. You’ll tackle questions spanning budget allocation, channel attribution, SEO, AEO, cross-product activation, bundled offerings, and the full self-serve journey from first touch through activation and viral expansion.

You’ll be embedded in a cross-functional pod aligned to a Route to Market, working closely with Engineering, Finance, Marketing, Design, and User Research. With direct access to the leaders setting strategy, you’ll serve as the go-to data partner for acquisition: getting into the technical details, translating complex findings into clear recommendations on channel optimization, budget decisions, and new growth areas.

This role is for a hands-on data scientist who thrives in a fast-moving environment, enjoys solving complex growth problems, and wants their work to measurably influence outcomes across products, audiences, and go-to-market motions.

What you’ll do
  • Be the go-to data person working directly with our Acquisition Marketing team, helping drive the efficacy of their marketing spend across our core paid and organic channels. This role is for someone who wants to be extremely hands-on, enjoys partnering cross-functionally with marketing peers, and wants to get deep into the technical weeds to find the best recommendations to ensure we optimize every marketing dollar we spend.

  • Be the embedded data science partner for the Superhuman Acquisition Marketing team — shaping channel strategy, budget allocation, prioritization, and roadmap decisions with evidence, not just fielding ad hoc requests.

  • Define and own the metrics that matter for Acquisition: LTV/CAC, new user growth, lifetime value, and web conversion rates to ensure we are responsible with our ad spend and driving continued conversion optimization.

  • Design and run incrementality tests across our most critical acquisition channels like Google, Meta, and YouTube.

  • Find opportunities for new user growth through budget reinvestment, new acquisition sources, international expansion, and website optimization.

  • Partner with our Acquisition, Engineering, Design, User Research, and Finance teams to build functional roadmaps for optimization of our acquisition channels across paid and organic sources.

  • Use data to craft a narrative, tell a story, and influence decisions to improve the efficiency of our ad channels and drive meaningful new user growth.

Qualifications
  • You have 7+ years of data science experience and a track record of driving measurable impact for business and customers.

  • Advanced expertise in experimentation and causal inference, including designing incrementality tests and translating results into acquisition investment decisions.

  • Demonstrated ability to develop marketing mix and budget allocation models that measure channel effectiveness, identify diminishing returns, and optimize acquisition spend across channels.

  • You have strong applied statistics skills and machine learning skills, and you use them to drive product and growth decisions.

  • You influence cross-functional partners and turn technical insight into action through clear communication, empathetic building, and openness to ideas from anywhere.

  • You’re a self-starting, creative problem-solver who distills problems to their core and thrives with ambiguity.

  • You’re comfortable using AI-assisted development tools like Claude Code or Codex to move faster, and you have the judgment to validate and supervise their output.

  • You have a bachelor’s degree in a quantitative field (statistics, mathematics, economics, computer science, data science, or a similar field); an advanced degree or equivalent practical experience is preferred.

Nice to haves:

  • Familiarity working with ad platforms across Google, Meta, and YouTube.

  • Experience with SEO and AEO optimization and organic acquisition channels.

  • You’re familiar with experimentation platforms such as Statsig and modern data stacks such as Databricks.

  • You have experience working at a fast-growing startup, on AI-native consumer products, and/or in B2B/SaaS.

Compensation and Benefits

Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:

  • Excellent health care (including a wide range of 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, and flexible sick time

  • Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)

  • Annual professional development budget and opportunities

Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.

Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.

We encourage you to apply

At Superhuman, we value our differences, and we encourage all to apply—especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).

 

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