Mgr, Commercial Data Analytics - AI/ML

Edwards Lifesciences • Irvine, CA

5d • $121,000 - $171,000 • Onsite

About The Position

Aortic stenosis impacts millions of people globally, yet it often remains under-diagnosed and under-treated. 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. As a Manager, Commercial Data Analytics – AI/ML you will infuse advanced AI and ML expertise into our analytics ecosystem by establishing technical leadership, defining AI strategy, and driving execution to accelerate insight generation & elevate our analytical capabilities. This role will be onsite at our Irvine, CA HQ. How you’ll make an impact: Serve as the team’s AI SME, guiding strategy, best practices, and technical direction. Identify and prioritize high impact AI opportunities across analytics workflows. Determine operational feasibility by evaluating analysis, problem definition, requirements, solution design, and proposed technical approaches Establish standards for model development, evaluation, documentation, and governance. Lead the design, development, and deployment of AI solutions at scale in partnership with business SMEs, data scientists, and engineering teams. Ensure successful delivery of end to end AI/ML initiatives, accountable for project scope and milestones. Mentor and upskill analysts, engineers, and business teams on AI/ML concepts and tooling. Develop, productionize, and operationalize ML/LLM models Collaborate with data engineering to build and maintain robust data/model pipelines for training, testing, serving, and monitoring ML/LLM models. Improve model efficiency, cost, scalability, and reliability. Perform feature engineering, experimentation, validation, and performance monitoring Build and deploy generative AI tools for defined business use cases Prototype, evaluate, and tune LLM based agents for self serve analytics and knowledge retrieval Implement governance (RBAC, guardrails, audit logs) Stay current with GenAI and traditional ML research and incorporate advancements into our roadmap. Collaborate with analytics, engineering, and business SMEs to ensure solutions drive measurable value. Ensure models and code are well documented and adhere to engineering best practices. Bring a self-driven, curious mindset to the team; proactively identify opportunities to improve processes, challenge existing approaches, and drive innovation.

Requirements

• Bachelors Degree in related field with 8 years of pervious related work experience or equivalent work experience based on Edwards criteria, or Master’s Degree with 6 years of pervious related work experience or equivalent work experience based on Edwards criteria
• Clinical experience (e.g., cardiology, clinics) or equivalent work experience based on Edwards criteria

Nice To Haves

• Proficiency in programming languages such as Python, Java, C++, or similar
• Experience with deploying AI/ML models to production systems
• Experience with AWS or Cloud Infrastructure Services
• Experience in a leadership or senior technical role, driving AI/ML strategy.
• Solid experience with version control systems (Git) and agile development methodologies
• Experience with ML frameworks and libraries like TensorFlow, PyTorch, Keras, Scikit-Learn or similar frameworks
• Solid experience with deep learning techniques (e.g., CNNs, RNNs, GANs, etc.).
• Familiarity with healthcare, claims, EHR, or commercial datasets
• Extensive troubleshooting/debugging skills
• Excellent analytical, detail-oriented, organized and information seeking skills
• Excellent organization and time management skills
• Excellent written and verbal communication skills and interpersonal relationship skills including negotiating and relationship management skills with ability to drive achievement of objectives
• Ability to manage multiple tasks and work towards long-term goals
• Strict attention to detail
• Ability to interact professionally with all organizational levels
• Ability to manage competing priorities in a fast paced environment
• Adhere to all company rules and requirements (e.g., pandemic protocols, Environmental Health & Safety rules) and take adequate control measures in preventing injuries to themselves and others as well as to the protection of environment and prevention of pollution under their span of influence/control

Responsibilities

• Serve as the team’s AI SME, guiding strategy, best practices, and technical direction.
• Identify and prioritize high impact AI opportunities across analytics workflows.
• Determine operational feasibility by evaluating analysis, problem definition, requirements, solution design, and proposed technical approaches
• Establish standards for model development, evaluation, documentation, and governance.
• Lead the design, development, and deployment of AI solutions at scale in partnership with business SMEs, data scientists, and engineering teams.
• Ensure successful delivery of end to end AI/ML initiatives, accountable for project scope and milestones.
• Mentor and upskill analysts, engineers, and business teams on AI/ML concepts and tooling.
• Develop, productionize, and operationalize ML/LLM models
• Collaborate with data engineering to build and maintain robust data/model pipelines for training, testing, serving, and monitoring ML/LLM models.
• Improve model efficiency, cost, scalability, and reliability.
• Perform feature engineering, experimentation, validation, and performance monitoring
• Build and deploy generative AI tools for defined business use cases
• Prototype, evaluate, and tune LLM based agents for self serve analytics and knowledge retrieval
• Implement governance (RBAC, guardrails, audit logs)
• Stay current with GenAI and traditional ML research and incorporate advancements into our roadmap.
• Collaborate with analytics, engineering, and business SMEs to ensure solutions drive measurable value.
• Ensure models and code are well documented and adhere to engineering best practices.
• Bring a self-driven, curious mindset to the team; proactively identify opportunities to improve processes, challenge existing approaches, and drive innovation.

Benefits

• Aligning our overall business objectives with performance, we offer competitive salaries, performance-based incentives, and a wide variety of benefits programs to address the diverse individual needs of our employees and their families.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager