• Design, build, and refine machine learning models that identify members at high risk for costly MSK interventions using claims, EMR, and enriched external data. • Own the technical architecture for Predict's data pipelines, ensuring reliable ingestion, transformation, and delivery of healthcare data at scale. • Establish and maintain ML ops practices—model versioning, monitoring, retraining pipelines, and performance tracking. • Conduct rigorous analysis of algorithm performance, cost curve impact, and ROI delivered to clients. • Stay current on healthcare data standards, regulatory requirements, and industry best practices. • Work closely and collaboratively with Sword’s Data team to ensure Predict’s work is embedded within the Tech team’s overall infrastructure and best practices. • Manage, mentor, and grow a team of data scientists and data engineers. • Set clear goals, provide regular feedback, and create development opportunities for each team member. • Foster a culture of intellectual rigor, collaboration, and continuous improvement. • Hire additional team members as Predict scales. • Serve as Predict's technical subject matter expert in client meetings, sales cycles, and implementation discussions. • Translate complex data science concepts into clear, compelling narratives for non-technical audiences. • Partner with customer success and sales teams to demonstrate Predict's value proposition and build client confidence. • Support business reviews, QBRs, and strategic discussions with data-driven insights alongside our Health Economics & Customer Insights team. • Work closely with product and engineering teams to align Predict's technical roadmap with platform strategy. • Collaborate with health economics to validate clinical and financial outcomes. • Partner with data access and integration teams to expand the data assets available for Predict models.

• Develop new educational products based on insights, stakeholder interviews and validation with target audiences. • Lead co-creation processes with partner institutions, aligning technical, academic and market requirements. • Translate strategic concepts into comprehensive documentation, including pedagogical specifications, marketing guidelines and enablement materials for internal teams (sales, marketing, content). • Define course positioning and value proposition, linking product attributes to market needs and competitive differentiators. • Monitor the course lifecycle, collaborating on updates, maintenance and portfolio evolution initiatives. • Analyze market, competitor and product performance data to recommend adjustments and new opportunities.

• Engaging with sales leads as a “human explicability layer,” up-leveling understanding for non-technical audiences to ensure that complex underwriting results are communicated clearly to drive sales. • Validating and maintaining the data pipelines and collateral shared between the Data Science and growth teams. • Helping us refine the competitiveness of our value-based care contracts by anticipating stakeholder needs and providing strategic guidance. • Ensuring quality and availability of various data sources. • Leveraging a deep understanding of ML concepts to consult on the application of payment models. • Designing and engineering analytics tooling to stress-test our underwriting outputs. • Evaluating vendors and technologies to help us better understand our customers and the market.

• Drive foundation models for wearable biosignals, setting standards for reusable representations, tooling, and evaluation adopted across multiple health features. • Design, implement, and validate deep learning approaches for large‑scale physiological time‑series (e.g., PPG, motion, temperature), including self‑supervised and multimodal pretraining; deliver adapters/probes for diverse downstream tasks. • Lead scientific publications from core modeling and validation work that advance understanding of human physiology and support Oura’s mission to improve health. • Build and operate scalable data generation, training, and inference pipelines to improve efficiency and reproducibility. • Lead collaborations with scientists, clinicians, engineers, and product teams to translate research advances into production features that bring value to Oura members.