We’re very proud of our achievements: In July 2024, we secured a $200M investment led by General Atlantic to help revolutionise women’s health, and became the first purely digital consumer women’s health app to achieve unicorn status!
We’ve had 400M+ downloads, have over 75M monthly users, are #1 by installs in the iOS Health category, hit 4.9 stars on the App Store (3M+ reviews), are backed by 9 VCs, had a 40% revenue increase last year, and topped a valuation of $1B.
We’re a growing, ambitious HealthTech business building the essential digital health partner of tomorrow to empower women, girls, and people who menstruate with the knowledge and support they need to stay well and live better.
Our cycle, ovulation and pregnancy tracking, educational content and anonymised community platform have been trusted for years by millions to help them feel more in control of their health every day. Now, we’re harnessing the power of data analytics and AI to build a smarter future, one where we all know our bodies better, with an aim to become the essential health partner to women worldwide.

YOU’LL BE RESPONSIBLE FOR:

• Running the day-to-day of the AI Foundation team - organising sprint work, running refinements, working with engineers including ML engineers, to write epics and stories, managing roadmap. Ability to work independently to unblock engineers and problem-solve.
• Working with 3rd parties developing Gen AI foundations and eco-system integrated into our architecture.
• Overseeing all specific work around prompt improvements,
• Building core foundations for LLM based products including evaluation frameworks, monitoring, analytics, ML pipelines, model APIs and integrations, system evaluation tools.
• Collaborating with a product designer, content designer and UX researcher - designing & delivering new features.
• Leading the team in establishing initiatives that are set and measured as part of the company OKR process
• Uncovering the user needs and problems, prioritising them using quantitative and qualitative data
• Managing clear, thoughtful product requirements and feature descriptions to help teams work efficiently and effectively
• Defining and monitoring product success metrics using data-driven goals
  

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