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Numan ищет специалиста по аналитике роста для ведения аналитики притока, конверсии, удержания и LTV. Вы будете проектировать и проводить эксперимименты по продукту, предложениям и ценовым политикам, а также анализировать экономика подписок в сотрудничестве с командами BI, финансов и маркетинга.
Требуется сильный опыт SQL, Looker, Python/R, навыки экспериментации и понимание экономики подписок. Возможности совместной работы и гибкий график с офисом в Лондоне предусмотрены.
Founded in 2018, we’ve already grown to be a 300+ team distributed across the globe, united by a singular mission: empowering people to take control of their health. Numan is transforming health: we’ve built a cutting-edge platform that integrates diagnostics, medication, supplements, digital programmes, and doctor consultations. Giving people the tools they need to maximise life.
Own the analytics for the growth squad across acquisition, conversion, retention and lifetime value, and be the go-to person for what’s working and why. Design, run and evaluate experiments on the product, propositions, offers and pricing. That includes A/B tests and holdouts that measure true incrementality, not just uplift of a subset of customers. Leverage the Finance and Data Teams view of unit economics (CAC, contribution margin, LTV:CAC), adhering to the existing artifacts and definitions, and show how every initiative moves those numbers. Analyse marketing channel mix and acquisition efficiency with the marketing team, including attribution and spend allocation. Segment customers and prospects by persona, behaviour and expected value, and turn those segments into targeted propositions and journeys. Leveraging data science predictions where they can add value. Track early-journey behaviour such as first-month engagement, commitment take-up and early retention, and find the levers that set patients up for long-term success. Shape the growth roadmap with the Principal PM, sizing opportunities and prioritising by expected impact on tier-one metrics. Present results, wins and failures to leadership and stakeholders clearly and regularly, with a recommendation every time. Work with BI, data engineering, commercial and pricing, take ownership of a set of scorecard metrics, and be able to understand and articulate drivers to their movement and fluctuations. Keep all analysis and experimentation inside clinical, data protection and advertising rules, working with the clinical and compliance teams where appropriate.