• Work in the Data Science team developing advanced AI solutions to drive marketplace growth and efficiency, leveraging cutting-edge technologies including GenAI and LLMs. • You will build models, tinker around them to make them work, test them, and eventually deploy them to production. You will see your stuff in action, and you will be able to measure the true impact of your models (less expected, yet a requirement) • You will maintain strong relationships with stakeholders. This means asking a lot of questions to business people and translating their requirements into achievable projects. It also means collaborating with other teams, like infrastructure and data engineering, to get things done in an elegant and timely manner. • Partner with Engineering and Product to deliver solutions (customer-facing and platforms) to our customers (internal and end customers) • Work with Product Analytics to track the KPIs of different ML use cases and measure the impact on our customers. • Partner with the Experimentation team to integrate the KPIs and their proxies into the Experimentation (A/B testing) platform. • You will work in multi-functional teams, in a diverse, multinational environment, filled with people from Portugal, Bulgaria, Romania, Poland and Ukraine. • Most importantly, you will have fun working with us :)

• Analyze large-scale wearable and physiological time-series data (e.g., sleep, activity, HR/HRV, temperature) to answer focused research questions in sleep, women’s reproductive health, cardiometabolic health, and movement. • Summarize results in figures, tables, and short written reports for internal stakeholders and potential external dissemination (e.g., abstracts, posters, manuscripts). • Collaborate with Health Science, Data Science, and Product partners to translate findings into clear, actionable insights relevant to Oura members and future product features. • Support literature reviews and contextualization of findings within current evidence to strengthen research narratives.

• Build and maintain data pipelines integrating subscription and membership data from source systems to provide a complete view of the member lifecycle and value. Ensure data quality, lineage, and governance standards for membership data systems. • Build predictive models to understand drivers of member retention, churn, reactivation, and LTV by segment, channel, and cohort. • Lead the design, implementation, and analysis of A/B tests and other experiments across pricing, packaging, and lifecycle communications to quantify impact and inform membership strategy and roadmap decisions. • Partner with Marketing, Finance, and Product teams to design and evaluate offers that improve acquisition efficiency and member retention, and to integrate these learnings into long-term strategic roadmaps. • Build models to optimize membership growth and retention, informing business decisions to strategically optimize financial decisions. • Leverage data engineering and analytical skills to transform data into actionable and reportable insights. • Develop dashboards and reporting tools to visualize membership funnel KPIs, cohort performance, and the impact of product/business changes on member outcomes.

• Design, develop, and deploy Machine Learning and Generative AI solutions • Build and optimize statistical and predictive models • Develop and manage LLM-based and agentic AI applications • Implement NLP/NLU solutions and chatbot applications using Dialogflow CX • Work with Vertex AI and other GCP services (GCS, Pub/Sub, Dataflow) • Utilize BigQuery for data analysis and model training workflows • Implement A/B testing and experimentation frameworks • Collaborate with engineering and product teams to deliver scalable solutions