Director – Statistical Innovation, Data Science

This is a fully remote position, open to applicants in Texas.

📋 Description

• Deliver senior-level quantitative guidance for clinical development and evidence generation.

• Implement statistical principles in study design, analysis, interpretation, and decision-making processes.

• Create and utilize advanced statistical models, including but not limited to linear and nonlinear, generalized linear, mixed-effects, hierarchical, longitudinal, survival, Bayesian, causal-inference, and simulation models.

• Analyze treatment responses, disease progression, heterogeneity, prediction, prognosis, benefit-risk assessments, and relationships among clinical, imaging, digital, patient-reported, and real-world data.

• Spearhead data science and machine learning initiatives for prediction, classification, clustering, patient stratification, signal detection, and high-dimensional data analysis.

• Develop and assess deep learning techniques for ophthalmic imaging and multimodal data.

• Compare traditional statistical methods, machine learning, and deep learning strategies based on scientific goals and regulatory requirements.

• Establish model development and validation protocols that encompass training, tuning, calibration, robustness, reproducibility, bias, interpretability, uncertainty, and performance monitoring.

• Investigate emerging methodologies, including generative AI, and convert prototypes into reusable analytical tools with appropriate human oversight and governance.

• Collaborate across various departments including Statistics, Clinical Development, Regulatory, Data Management, Digital, Quality, and Technology.

• Work alongside programmers, data scientists, machine learning engineers, and data engineers.

• Articulate quantitative concepts and model limitations to both technical and non-technical stakeholders.

• Represent Alcon in scientific, regulatory, and external collaborations.

• Mentor and nurture the development of quantitative scientists.

• Enhance organizational capabilities in statistical modeling, data science, machine learning, deep learning, reproducible research, and responsible AI.

• Contribute to the long-term vision, operational framework, and scientific trajectory of the Statistics organization.

⛳️ Requirements

• Bachelor’s Degree or equivalent years of directly related experience.

• Alternative qualification pathways include: high school +18 years, Associate degree +14 years, M.S. +7 years, or PhD +6 years.

• A minimum of 10 years of relevant experience.

• At least 6 years of proven leadership experience.

• Proficient in reading, writing, understanding, and communicating in English.

• An advanced degree (MSc or PhD) in Statistics or Biostatistics is preferred; a PhD in related quantitative fields may also be considered.

• Extensive knowledge in statistical inference and modeling, including linear, nonlinear, and other advanced statistical methodologies.

• Practical experience in data science, machine learning, and/or deep learning, ideally with clinical, biomedical, imaging, digital health, or other high-dimensional datasets.

• Proficient in R and/or Python.

• Experience with reproducible, version-controlled analytical processes and contemporary statistical/machine learning computing environments.

• Ability to assess the appropriateness of classical statistical models, machine learning, deep learning, or hybrid approaches.

• Experience in supporting clinical development, regulatory submissions or interactions, and scientific publications.

• Understanding of model validation, data integrity, and the evolving expectations for AI/ML in regulated settings.

🏝️ Benefits

• Focused growth and development opportunities.

• Health insurance.

• Life insurance.

• Retirement benefits.

• Flexible time off.

• Relocation assistance.

• Visa sponsorship.

• Travel up to 10%.