Sr. Associate I, Data Science

At Alcon, we are passionate about enhancing sight and helping people see brilliantly. The Sr. Associate I, Data Science is responsible for developing methods, processes, and systems to consolidate and analyze diverse and unstructured data sources, generating actionable insights for client services and product enhancement. The role leverages traditional AI, machine learning, and generative AI techniques, including Large Language Models (LLMs), to solve complex business problems and drive innovation.

Key Responsibilities:

Data Science & AI Development

• Develop, test, and select machine learning models for data science projects, making decisions on model selection and data processing methods.
• Analyze large datasets to extract actionable insights and support informed decision-making.
• Apply AI techniques including Time Series analysis, Computer Vision, NLP, and generative AI to generate innovative solutions.
• Build mathematical optimization models using tools like CVXPY.
• Ensure model robustness by cross-validating and testing generalizability.

Collaboration & Project Management

• Collaborate with senior data scientists and stakeholders to achieve project objectives.
• Delegate tasks to junior data analysts or data scientists to ensure successful project completion.
• Manage project priorities, timelines, and technical constraints effectively.

Innovation & Continuous Improvement

• Explore and recommend new AI and data science solutions to improve team capabilities and processes.
• Document and communicate findings, results, and recommendations to both technical and non-technical audiences.
• Support MLOps practices to deploy and maintain models in production environments.

Key Requirements/Minimum Qualifications:

• Strong analytical skills and technical problem-solving ability.
• Solid experience in building code and machine learning models.
• Experience with NLP and Computer Vision algorithms.
• MLOps experience for deploying and maintaining models.
• Experience with mathematical optimization models (e.g., CVXPY).
• Proficiency in Python, SQL, AWS, Tableau, Sagemaker, and related tools.
• Project management experience to oversee data science initiatives.
• Ability to cross-validate models and ensure their generalizability.