Applied AI Data Scientist – GenAI & Intelligent Automations

About the role

Alcon is seeking an Applied AI Data Scientist to develop Generative AI and machine‑learning solutions that drive real business impact across Commercial Operations. You will work closely with business stakeholders and engineering teams to turn AI concepts into production‑ready tools.

Key responsibilities

• Translate business needs into AI‑driven automation and decision‑support tools.
• Design and build LLM‑based applications such as copilots, workflow automations, and internal AI utilities.
• Apply machine‑learning techniques to improve reporting, forecasting, and operational efficiency.
• Experiment with Generative AI approaches (prompting, embeddings, structured outputs) and evaluate their performance.
• Collaborate with engineering to deploy AI solutions in production environments.
• Monitor solution performance, iterate, and ensure reliability over time.
• Communicate AI capabilities, limitations, and trade‑offs to non‑technical stakeholders.

Required profile

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics or a related field.
• 3+ years of experience in Data Science, Machine Learning, or Applied AI roles.
• Hands‑on experience with Generative AI or LLM‑based projects (academic, personal or professional).
• Proven track record developing data‑driven AI solutions in a business setting.

Required skills

• Strong proficiency in Python and SQL.
• Experience with machine‑learning model development.
• Familiarity with Generative AI tools and frameworks (e.g., OpenAI APIs, LangChain).
• Prompt design, embeddings, and retrieval‑based approaches.
• Evaluating outputs of AI systems.
• Working knowledge of cloud platforms, preferably AWS.
• Understanding of data pipelines and handling structured/unstructured data.

What we offer

• Opportunity to work on real‑world Generative AI use cases within a global eye‑care organization.
• Exposure to building AI‑driven solutions that directly impact commercial operations.
• Collaborative, inclusive culture that encourages technical growth.