Director, Advanced Manufacturing Analytics

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? We foster an inclusive culture and are looking for diverse, talented people to join Alcon. Alcon is accelerating its digital manufacturing ambitions, integrating modern operational technologies with enterprise digital systems to enable world‑class performance across its 16+ global manufacturing sites and across the full supply chain. Central to this transformation is the strategic development and deployment of insights and functionality on top the digital landscape.

The Director of Advanced Manufacturing Analytics will own the strategic development and deployment of advanced data analytics capabilities across a multi‑site manufacturing and supply chain network. This is a business- and application-focused role that identifies high‑value opportunities, rapidly pilots solutions, and scales proven capabilities to all sites by orchestrating internal data science and data engineering teams, site operations, and selected third‑party partners.

You will also serve as the business owner for global KPI dashboards, evolving them into predictive and prescriptive tools for metrics such as Purchase Price Variance (PPV), Inventory, Yield, OEE, Schedule Attainment, and more.

Manage a 2–3-year capability roadmap aligned to manufacturing priorities

Define a portfolio of scalable use cases with clear value hypotheses, ROI models, and adoption plans

Rapid Pilots → Scaled Deployment

Stand up lean pilots in weeks, not months, to gain quick insight into the rapidly evolving AI/ML and visualization landscape

Codify pilots into repeatable playbooks and templates; drive scale‑up to all eligible sites

Own business definition, data lineage, and governance for global dashboards (e.g., PPV, inventory, OEE)

Extend dashboards with advanced capabilities including forecasting, anomaly detection, scenario simulation, and automated alerts

Identify and manage 3rd‑party providers to complement internal teams to speed up time‑to‑value

Structure outcome‑based SOWs, price‑to‑value models, and success criteria

Influence data architectures to create appropriate capabilities and scale that meet manufacturing’s requirements

Ensure operational AI/ML has appropriate controls in place to manage quality and business risks

Build solutions that scale natively by deeply understanding use‑cases and partnering with global and local teams for tech stack standardization

Build site champion networks, training, and hiring/upskilling plans to drive sustained use of solutions and talent pipeline

Build and maintain a ranked use‑case portfolio with quantified value, complexity, time‑to‑impact

Align with Finance/Procurement/Operations on PPV, inventory yield value levers and measurement

Publish a quarterly “State of Data Science in Manufacturing” progress and impact report

Lead ideation → prioritization → pilot → implementation → scale of use cases

Define acceptance criteria and guardrails for site rollout (data readiness, process readiness, training)

Own global business requirements and success metrics; partner with IT, vendors, and sites for technical delivery

Serve as the Product Owner for global KPI dashboards

Establish KPI definitions, visualization guidelines, and drill‑down standards

Implement advanced KPIs capabilities like predictive, scenario, and alerting concepts

Build trust with Site Leaders, Supply Chain, Procurement, Quality, Finance, and IT/Data teams

Select and manage vendors; negotiate deliverables, SLAs, and…