Director, Statistical Innovation and Data Science

At Alcon, we're passionate about enhancing sight and helping people see brilliantly. With more than 25,000 associates, we innovate fearlessly, champion progress, and act swiftly to impact global eye health. We foster an inclusive culture, recognizing your contributions and offering opportunities to grow your career like never before. Together, we make a difference in the lives of our patients and customers. Are you ready to join us?
As Director, Statistical Innovation and Data Science, you will provide strategic and scientific leadership at the intersection of statistics, statistical modeling, data science, machine learning (ML), deep learning, and AI for evidence generation. You will be a quantitative scientist who combines rigorous statistical thinking with modern computational methods to solve complex scientific problems and translate innovation into reproducible, validated, and scalable capabilities for a regulated environment.

This role is on-site in our Fort Worth, Texas (or remote in the US) location and a typical day would include:

• Provide senior quantitative leadership for clinical development and evidence generation, applying sound statistical principles to study design, analysis, interpretation, and development decisions.
• Develop and apply advanced statistical models, including linear and nonlinear models, generalized linear models, mixed-effects and hierarchical models, longitudinal and survival models, Bayesian methods, causal inference, and simulation.
• Use statistical modeling to characterize treatment response, disease progression, heterogeneity, prediction, prognosis, benefit-risk, and relationships among clinical, imaging, digital, patient-reported, and real-world data.
• Lead application of data science and ML methods for prediction, classification, clustering, patient stratification, signal identification, and high-dimensional data analysis.
• Develop and evaluate deep-learning approaches, including applications to ophthalmic imaging and multimodal data integrating images with clinical and other complex data sources.
• Compare classical statistical models, ML, and deep-learning approaches based on the scientific objective, assumptions, uncertainty, interpretability, validation, generalizability, and intended use rather than technological novelty.
• Establish rigorous model-development and validation practices covering training, tuning, calibration, robustness, reproducibility, bias, interpretability, uncertainty, and performance monitoring as appropriate to context of use.
• Identify and evaluate emerging approaches, including generative AI, and translate high-value prototypes into reusable analytical capabilities with appropriate human oversight and governance.
• Partner across Statistics, Clinical Development, Regulatory, Data Management, Digital, Quality, and Technology, and collaborate effectively with programmers, data scientists, ML engineers, and data engineers.
• Communicate complex quantitative concepts and model limitations clearly to technical and nontechnical audiences; represent Alcon in scientific, regulatory, and external collaborations.
• Mentor and develop quantitative scientists and strengthen organizational capability in statistical modeling, data science, ML, deep learning, reproducible research, and responsible AI.
• Contribute to the long-term strategy, operating model, and scientific direction of the Statistics organization.

Preferred Qualifications

• Advanced degree (MSc or PhD) in Statistics or Biostatistics preferred, PhD in closely related quantitative disciplines may be considered.
• Deep expertise in statistical inference and modeling, with demonstrated experience in linear and nonlinear modeling and other advanced statistical methods.
• Applied expertise in data science, machine learning, and/or deep learning, preferably using clinical, biomedical, imaging, digital-health, or other high-dimensional data.
• Proficiency in R and/or Python and experience with reproducible, version-controlled analytical workflows and modern statistical/ML computing environments.
• Demonstrated ability to determine when classical statistical models, ML, deep learning, or hybrid approaches are most appropriate for a scientific question.
• Experience supporting clinical development, regulatory submissions or interactions, and scientific publications; knowledge of model validation, data integrity, and evolving expectations for AI/ML in regulated environments.

What You’ll Bring To Alcon:

• Bachelor’s Degree or Equivalent years of directly related experience (or high school +18 yrs; Assoc.+14 yrs; M.S.+7 yrs; PhD+6 yrs)
• The ability to fluently read, write, understand and communicate in English
• 10 Years of Relevant Experience
• 6 Years of Demonstrated Leadership
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How You Can Thrive at Alcon:

• See your career like never before with focused growth and development opportunitiesJoin Alcon’s mission to provide outstanding, innovative products and solutions to improve sight, improve lives, and grow your career!
• Alcon provides a robust benefits package including health, life, retirement, flexible time off and much more.
• Travel - up to 10%
• Relocation - Yes
• Sponsorship Yes

Alcon Careers

• See your impact at alcon.com/careers

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ALCON IS AN EQUAL OPPORTUNITY EMPLOYER AND PARTICIPATES IN E-VERIFY

Alcon takes pride in maintaining an inclusive environment that values different perspectives and our policies are non-discriminatory in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status. Alcon is also committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an email to and let us know the nature of your request and your contact information.

Summary

• Location: Fort Worth, Texas; Fort Worth - Main
• Type: Full time