• Solve real business problems with data: Own end-to-end data science work, from problem framing and data exploration to modeling, validation, and production impact. • Lead high-impact initiatives: Drive complex efforts such as vendor leakage detection and prevention, delivering measurable revenue or cost improvements. • Innovate on methods and approaches: Go beyond standard analyses by developing new metrics, models, or workflows when existing approaches fall short. • Build and productionize models: Design, build, and support production ML or LLM-powered solutions in collaboration with engineering and product partners. • Work deeply with data: Use SQL fluently to explore large datasets, build reliable data assets, and validate results. • Influence cross-functionally: Partner with Product, Engineering, Finance, and Operations to align on goals, tradeoffs, and execution plans. • Set technical direction (especially at L7): Raise the bar for data science quality, scalability, and impact across the organization through mentorship, design reviews, and technical leadership.

• Translate medical policy into executable logic • Build robust clinical feature pipelines • Own measurement, evaluation, and continuous quality improvement • Establish engineering frameworks and tooling • Partner deeply with domain experts

• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments • Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights • Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes • Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. • Identify opportunities, advocate for new solutions and build momentum cross-functionally to move ideas forward that are grounded in data. • Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments • Translate complex concepts into implications for the business via excellent communication skills, both verbal and written • Understand what matters most and prioritize ruthlessly • Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

• As a Data Scientist specializing in medical document analysis, you will work at the forefront of healthcare NLP. • You will design, implement, and evaluate advanced natural language understanding (NLU) systems that interpret complex clinical text and support data-driven medical decision making. • This includes developing models grounded in transformers, generative AI, and research-oriented neural architectures. • You will collaborate closely with clinical domain experts, fellow data scientists, ML engineers, and product teams to bring research prototypes into production systems. • You will explore new modeling approaches, optimize training pipelines, and contribute to the long-term direction of Solventum’s deep learning portfolio.