Edwards Lifesciences is a global leader in patient-focused innovations for structural heart disease. Join the Global Health Economics & Reimbursement (GHER) Biostatistics team and help generate rigorous evidence that informs healthcare decision-making and supports patient access to Edwards’ innovative technologies. Under the direction of the Lead Biostatistician, the Senior Biostatistician will collaborate with health economists, clinicians, epidemiologists, and cross-functional partners to design and execute real-world evidence and health outcomes research, apply statistical methods to complex healthcare data, and communicate meaningful insights. Through this work, the Senior Biostatistician will contribute to Edwards’ mission to improve the lives of patients with cardiovascular disease. This position is based at Edwards’ corporate headquarters in Irvine, California. How you will make an impact: Under the direction of the Lead Biostatistician, design and execute real-world evidence, health economics, and outcomes research studies aligned with market access and business needs Develop Statistical Analysis Plans (SAPs), study specifications, endpoint and cohort definitions, and programming requirements for assigned observational research studies Apply advanced statistical and epidemiologic methods to claims, electronic health records, registries, clinical trial-linked data, and other real-world data sources to address confounding, selection bias, missing data, and other limitations inherent in observational research Develop and execute reproducible, well-documented statistical programs for planned, exploratory, and ad hoc analyses, with appropriate quality control Review study protocols, research plans, and data specifications, and provide statistical input on study design, data feasibility, cohort and endpoint definitions, analytic methods, and interpretation Identify meaningful patterns and evidence gaps to inform research priorities and strategic decision-making Interpret complex findings and communicate their implications, assumptions, and limitations clearly to technical and nontechnical audiences Perform independent validation of statistical programs, analyses, tables, figures, study reports, abstracts, manuscripts, and other scientific deliverables Author or contribute to statistical sections of study protocols, SAPs, study reports, abstracts, conference presentations, manuscripts, and responses to scientific review Partner with cross-functional teams to clarify evidence needs, assess data feasibility, and ensure analyses are scientifically sound and accurately presented Serve as a statistical resource to colleagues and cross-functional partners, providing guidance on analytical methods and interpretation as appropriate. Stay current with developments in biostatistics, epidemiology, causal inference, real-world evidence, and medical technology through literature review, professional meetings, workshops, and continuing education What you will need (Required): Master’s degree or equivalent in Statistics, Biostatistics or a related quantitative field with at least 2 years of relevant analytical experience required OR Ph.D. or equivalent Statistics, Biostatistics or related field with internship, senior projects, or thesis in Statistics, Biostatistics or related field Required What else we look for (Preferred): Master’s Degree or Ph.D. in Epidemiology, Data Science, Health Economics or related quantitative field. Proficiency in SAS and/or R, including data management, statistical programming, and production of high-quality analytic outputs Strong foundation in applied statistics and observational research methods with the ability to select, implement, and explain appropriate analytic methods Ability to communicate findings clearly and collaborate effectively in a cross-functional environment Experience designing and analyzing real-world evidence studies using healthcare claims, electronic health records, registries, administrative data, or linked clinical and real-world data Knowledge of observational research methods, including confounding control, causal inference, missing-data methods, and sensitivity analyses Experience with longitudinal analysis, generalized linear models, GEE, mixed models, survival and competing-risk methods, propensity score methods, and sample size or power calculations Experience working with large, complex datasets and creating reproducible, well-documented analytic workflows Familiarity with health economic analyses, predictive modeling, machine learning, or simulation methods Experience with SQL, Python, version control, Tableau, Power BI, or related analytic and visualization tools Experience contributing to peer-reviewed publications, conference abstracts, posters, or presentations Strong written, verbal, and visual communication skills, with excellent organization, attention to detail, and the ability to manage multiple priorities 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. For California (CA), the base pay range for this position is $119,000 to $168,000 (highly experienced). The pay for the successful candidate will depend on various factors (e.g., qualifications, education, prior experience). Applications will be accepted while this position is posted on our Careers website. Edwards is an Equal Opportunity/Affirmative Action employer including protected Veterans and individuals with disabilities. Edwards Lifesciences is the leading global structural heart innovation company, driven by a passion to improve patient lives. Through breakthrough technologies, world-class evidence and partnerships with clinicians and healthcare stakeholders, our employees are inspired by our patient-focused culture to deliver life-changing innovations to those who need them most.

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