Job Specifications
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.
Superhuman team members for this role must be based in the San Francisco Bay Area.
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, Coda’s collaborative workspaces, 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
To achieve our ambitious goals, we’re looking for experienced Data Scientists to join our Product and Growth Data Science teams. At Superhuman, Data teams are trusted subject matter experts who uncover new insights to inform marketing, product, and growth strategies that drive outcomes at the highest levels of the company. We have large datasets and are seeking individuals with excellent technical and analytical skills who can break down complex business problems and provide solutions with high visibility and impact for the company.
Growth Data Scientists partner closely with our product, engineering, growth, and/or lifecycle marketing stakeholders. They are responsible for designing and overseeing product experiments, as well as conducting complex analyses to inform product strategy through advanced analytics and machine learning. The ideal candidate will have a strong track record of delivering impactful analytical projects within the Growth domain and partnering with cross-functional peers to guide and influence decision-making.
Product Data Scientists are responsible for evaluating the quality of the Superhuman products, end-to-end, from the usefulness and accuracy of our text suggestions to the stickiness of new AI features and user experiences and interfaces. Product Data Scientists serve as trusted experts for our team of product managers and product leaders to help drive product strategy based on data. They work with the PMs, engineering managers, software engineers, designers, ML engineers, and UX researchers who build new features and improve existing ones to ensure that our product development efforts are data-driven and that we are experimenting rapidly and effectively. This role provides an opportunity for ownership over important parts of the Superhuman product experience and broad cross-functional collaboration opportunities with our growth, ML/AI, and enterprise data science teams.
Superhuman’s engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure.
As a Data Scientist, You Will
Partner closely with growth product, engineering, design, growth, and lifecycle marketing teams.
Build new metrics that deliver insights and expand our understanding of our users.
Mine large datasets to uncover patterns across our users’ behaviors, enabling new marketing touchpoints.
Design and run experiments to improve the user experience across our user lifecycle.
Optimize marketing across our email, in-product, and push channels to ensure we send relevant, timely, personalized touchpoints to our users.
Guide your stakeholders’ decisions and roadmaps with informative, evidence-based decision-making.
Take on a broad and challenging scope of work in a rapidly evolving company.
Drive impact through statistical methodologies, algorithms, and measurement frameworks.
Collaborate with other data scientists to continue improving the methodologies and practices used across the team, leveraging the latest technological developments in the industry.
Develop causal inference and machine learning models that deepen user insights and drive engagement, retention, and feature adoption.
Qualifications
5+ years of relevant work experience with a proven track record of applying data science methods that drive impact.
Fluency in Python and SQL with strong data exploration and manipulation skills.
Has a firm grasp on how to best dig into and analyze datasets that influence the product roadmap.
Strong understanding of statistical methods, including causal inference, to support data-driven decision-making.
Is well-versed in hypothesis A/B testing as well as exploratory methods, and can translate business questions into sound experimental frameworks and measurement plans.
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