Data Scientist

Join the Sleep Fitness Movement

At Eight Sleep, we’re on a mission to fuel human potential through optimal sleep. As the world’s first sleep fitness company, we’re redefining what it means to be well‑rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data‑driven recovery experience.

We are trusted by high performers, professional athletes, and health‑conscious consumers in over 30 countries worldwide. Recognized as one of Fast Company’s Most Innovative Companies in 2019, 2022, and 2023, and twice named to TIME’s “Best Inventions of the Year.” We operate like a high‑performance team: fast, focused, and motivated by impact. We don’t just ship; we iterate, refine, and obsess over the details that help our members sleep better and wake up stronger.

We operate with intensity because our mission demands it. At Eight Sleep, we bring the same mindset as the world’s top performers: focused, relentless, and always pushing to be in the top 1% of our craft. Think Kobe Bryant’s mamba mentality, applied to bold ideas, next‑gen tech, and flawless execution. This isn’t a 9‑to‑5. Our team is deeply committed, often putting in 60+ hours a week –not because we’re told to, but because we’re invested.

We’re here to build fast, push limits, and deliver without compromise. If you thrive under pressure and want to do the most meaningful work of your career, you’ll feel right  you’re looking for something easier –this isn’t it.

We’re seeking a Data Scientist to join our Data & Analytics team within the Growth organization. This isn't a typical analyst role – you'll be the lead growth data scientist at Eight Sleep, owning complex forecasting challenges that directly impact our supply chain, marketing spend, and business growth. The ideal candidate has deep experience with time series forecasting, experimentation design, and translating ambiguous business problems into data‑driven solutions.

• Advanced demand forecasting models to solve our biggest operational challenge: eliminating stock‑outs during peak periods (Black Friday, holidays) while avoiding over committing capital on inventory
• Marketing spend optimization algorithms that go beyond our current Prophet model, incorporating seasonality, macro trends, and cross‑channel effects to improve our CAC targeting
• Experimentation frameworks for incrementality testing across our marketing channels (Meta, Google, You Tube) with proper statistical rigor
• Marketing attribution models that handle our complex customer journey and multi‑touch attribution challenges

• 5+ years of data science experience with demonstrable impact on business‑critical forecasting and optimization problems
• Forecasting expertise – you’ve built production models that handle seasonality, growth trends, and external factors. Bonus points if you’ve worked with Prophet and know its limitations
• Strong experimentation background – you can design proper A/B tests, understand incrementality measurement, and have experience with marketing mix modeling
• Advanced Python/R skills plus expert SQL – you’ll be building production pipelines and complex models, not just ad‑hoc analysis
• High ownership mentality – comfortable with ambiguous problems and 60+ hour weeks during critical periods. This is a startup where your work directly impacts our trajectory
• Business acumen – you can translate between technical solutions and business stakeholders (Growth, Finance, Operations teams)
• Strong written and verbal communication – you can translate complex findings into actionable insights. Your written and verbal communication skills are excellent
• High sense of agency – you are an independent self‑starter who thrives in a fast‑paced environment and is comfortable owning a high level of responsibility

We will hire for this role anywhere in the US, but working hours will be EST.

Employees approved for remote work must perform their duties from a single, company‑approved based location.