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Oura is seeking a Senior Data Scientist to partner with the Member Experience (MX) organization to build systems, analytics, and models that improve member support across the Oura Ring ecosystem. This full-stack data science role sits within Data Science and works across MX analytics, quality, business systems, and operations to translate member support data into actionable decisions and better outcomes.
Key responsibilities include: building and maintaining a quality scoring classifier for support interactions using NLP and LLM-based approaches with evaluation and monitoring; designing new support performance metrics beyond traditional volume and satisfaction reporting (member effort, case complexity); enhancing forecasting models for support volume, capacity, and staffing demand; creating the data layer linking support interactions to member identities and lifecycle data to analyze quality, NPS, CSAT, retention, and churn; partnering with MX and cross-functional teams to define problems and translate business needs into scalable solutions; building recurring dashboards and decision-support systems for visibility into support quality and member outcomes; and leveraging SQL, Python, and data engineering skills to transform operational data into trusted, actionable insights.
Required qualifications: 6+ years in data science, machine learning, or advanced analytics with a track record of owning high-impact business problems end-to-end; strong SQL and Python proficiency with experience building analytical data models, ML workflows, and production-quality measurement systems; experience building and evaluating NLP or LLM-based models including open-source workflows and model quality monitoring; forecasting, time series modeling, or quantitative methods experience for operational planning; strong data engineering intuition for unifying and transforming data across systems; experience with modern cloud and data platforms (Databricks, AWS, dbt, Snowflake); proven ability to communicate complex analytical concepts to non-technical partners; and experience working with cross-functional, distributed teams in fast-moving environments.
Nice-to-have skills include experience with customer support, contact center, CX, or operations data; defining or operationalizing business KPIs for vendor management or service quality; and background in subscription, membership, consumer technology, or digital health businesses.
