Director, Data Science & Optimization

Alcon Research•Fort Worth, TX

12d

About The Position

At Alcon, we are driven by the meaningful work we do to help people see brilliantly. We innovate boldly, champion progress, and act with speed as the global leader in eye care. Here, you’ll be recognized for your commitment and contributions and see your career like never before. Together, we go above and beyond to make an impact on the lives of our patients and customers. Are you ready to join us? We foster an inclusive culture and are looking for diverse, talented leaders to join Alcon. ITCI is accelerating Alcon’s digital and AI transformation through advanced analytics, enterprise AI, modern data platforms, and innovative business solutions. The Director, Data Science, leads teams of data scientists and engineers to deliver scalable AI, machine learning, optimization, and analytics solutions that drive business performance. This role partners across business and technology function to solve complex challenges, enable data-driven decisions, and deliver measurable enterprise impact. In this role, a typical day will include: Define and execute the data science roadmap aligned with ITCI and enterprise priorities. Build, mentor, and develop a high-performing data science organization. Establish best practices for data science, machine learning, optimization, and AI development. Drive a culture of innovation, accountability, and continuous improvement. Partner with senior business leaders to identify high-value opportunities. Lead the design, development, deployment, and monitoring of advanced analytics and AI solutions. Drive adoption of machine learning, generative AI, predictive analytics, decision science, and optimization capabilities. Ensure solutions deliver measurable business value and operational impact. Oversee model governance, validation, explainability, and performance management. Champion AI solutions that augment decision making and improve productivity. Serve as a trusted advisor to business and technology leaders. Collaborate with Data Engineering teams to ensure scalable, AI-ready data foundations. Partner with Business Technology Partners, Product Owners, and business stakeholders to define requirements and success metrics. Communicate insights and recommendations to executive audiences. Establish KPIs to measure adoption, impact, and value realization. Ensure efficient delivery of projects through standardized methodologies and governance. Promote effective experimentation frameworks and data-driven decision making. Drive continuous improvement in analytical capabilities and delivery processes. Create growth opportunities through mentoring, coaching, and technical leadership. Foster collaboration across global teams and functions. Mainly supports AI initiatives in Supply Chain - (other projects as needed)

Requirements

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

Nice To Haves

Experience in healthcare, medical devices, pharmaceuticals, manufacturing, supply chain environments.
Experience with large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI solutions.
Familiarity with MLOps, DevOps, and enterprise AI governance frameworks.
Master's degree or PhD in Data Science, Statistics, Operations Research, Computer Science, Engineering, Applied Mathematics, or a related quantitative field.
10+ years of experience in analytics, data science, machine learning, or AI.
5+ years of experience leading high-performing analytics or data science teams.
Demonstrated experience delivering enterprise-scale AI, machine learning, and advanced analytics solutions.
Strong stakeholder management and executive communication skills.
Experience managing cross-functional teams and complex business initiatives.
Proficiency with Python, SQL, cloud-based analytics platforms, and modern machine learning frameworks.

Responsibilities

Define and execute the data science roadmap aligned with ITCI and enterprise priorities.
Build, mentor, and develop a high-performing data science organization.
Establish best practices for data science, machine learning, optimization, and AI development.
Drive a culture of innovation, accountability, and continuous improvement.
Partner with senior business leaders to identify high-value opportunities.
Lead the design, development, deployment, and monitoring of advanced analytics and AI solutions.
Drive adoption of machine learning, generative AI, predictive analytics, decision science, and optimization capabilities.
Ensure solutions deliver measurable business value and operational impact.
Oversee model governance, validation, explainability, and performance management.
Champion AI solutions that augment decision making and improve productivity.
Serve as a trusted advisor to business and technology leaders.
Collaborate with Data Engineering teams to ensure scalable, AI-ready data foundations.
Partner with Business Technology Partners, Product Owners, and business stakeholders to define requirements and success metrics.
Communicate insights and recommendations to executive audiences.
Establish KPIs to measure adoption, impact, and value realization.
Ensure efficient delivery of projects through standardized methodologies and governance.
Promote effective experimentation frameworks and data-driven decision making.
Drive continuous improvement in analytical capabilities and delivery processes.
Create growth opportunities through mentoring, coaching, and technical leadership.
Foster collaboration across global teams and functions.