Senior Data Scientist

Imagine how your ideas and expertise can change a patient’s life. We generate extensive clinical evidence to demonstrate the effectiveness and safety of our innovations and how our products transform patients’ lives. As part of our Clinical Affairs team, you’ll hone your scientific curiosity and passion for evaluating data to increase access to pioneering technologies for patients in need. In close partnership with principal investigators, dedicated medical professionals, patient advocacy groups, and regulatory authorities, you will drive the evidence needed to optimize patient outcomes.

Aortic stenosis impacts millions of people globally, yet it often remains under-diagnosed and undertreated. Edwards’ groundbreaking work in transcatheter aortic heart valve replacement (TAVR) pioneered an innovative, life‑changing solution for patients by offering heart valve replacement without the need for open heart surgery. Our Transcatheter Heart Valve (THV) business unit continues to partner with cardiologists and clinical teams to transform patient care with devices supported by clinical evidence.

It’s our driving force to help patients live longer and healthier lives. Join us and be part of our inspiring journey.

The Senior Scientist, Data — THV will drive measurable business and program impact by applying advanced analytics, machine learning, and generative AI to deliver high‑value insights and data‑driven recommendations. This role partners across diverse stakeholders to optimize decision‑making, enhance model performance, and innovate with emerging AI capabilities—including large language models (LLMs) and AI‑assisted development tools.

• Design, build, test, and optimize advanced machine learning models—including NLP, deep learning, and large language models—to support strategic use cases and business outcomes.
• Develop and refine complex algorithms; evaluate model results; generate actionable recommendations; and communicate findings to both technical and non‑technical audiences.
• Analyze, interpret, and report on complex data sets, algorithmic outcomes, and ML performance metrics.
• Cleanse, label, and validate both structured and unstructured data, ensuring accuracy, completeness, and model readiness.
• Experiment with new data sources and integrations to improve model performance and operational efficiency.
• Identify and implement analytics tools and platforms (Python, SQL, Power BI, etc.) to elevate the data science tech stack and accelerate productivity.

• Bachelor’s Degree in a related field (e.g., Computer Science, Engineering, Biostatistics, or a Scientific field), 4 years of previous experience
• Master’s Degree or equivalent in related field (e.g. Computer Science, Engineering, Biostatistics or Scientific), 3 years’ experience including either industry or industry/education
• Experience with machine learning techniques (e.g., clustering, decision tree learning, artificial neural networks, etc.) such as Boosting Model and Decision Forests
• Experience using statistical computer languages (e.g, R, Python, SQL, etc.) to manipulate large data sets
• Ability to effectively communicate information
  
  Experience with cloud services (e.g., AWS and Snowflake)

• Leverage generative AI tools (e.g., Github Copilot and Python LLM frameworks) to accelerate exploration, prototyping, and automation across data science workflows.
• Use AI‑assisted coding tools (e.g., Git Hub Copilot, SQL copilots, and generative Python assistants) to streamline development, documentation, and testing workflows.
• Author and maintain detailed design control documents, including algorithm requirements, validation plans, and risk assessment documentation.
• Support internal and external partners with analytics methodology, metrics, and reporting best practices.
• Work cross‑functionally with engineering, product, clinical, commercial, and external partners to translate business needs into robust analytical solutions.
• Provide technical guidance and mentorship to peers and partner teams on ML, LLMs, and responsible AI practices.
Aligning our overall business objectives with…