AI & Data Analytics Intern Optical Metrology

About Alcon:

Alcon helps people see brilliantly. As the global leader in eye care with a heritage spanning over 75 years, we offer the broadest portfolio of products to enhance sight and improve people’s lives. Our Surgical and Vision Care products touch the lives of more than 260 million people in over 140 countries each year living with conditions like cataracts, glaucoma, retinal diseases and refractive errors. Our more than 25,000 associates are enhancing the quality of life through innovative products, partnerships with Eye Care Professionals and programs that advance access to quality eye care. If you’d like to help us change the way the world sees, this is your chance to Be Brilliant!

Position Description:

Alcon is seeking an AI & Data Analytics Intern – Optical Metrology (Medical Devices) with strong skills in AI/ML, Python, SQL, R, and data analytics to support our contact lens R&D optical and dimensional characterization workflows. This intern will help design, improve, and automate data-processing pipelines from optical metrology instruments, enabling more efficient reporting, analysis, and decision-making.

Key Responsibilities:

• Optimize data flow pipelines from optical metrology instruments.
• Develop Python- and SQL-based data-processing scripts.
• Use R, Python, or SQL for statistical analysis.
• Apply AI/ML techniques to improve data quality and reporting.
• Build automated reporting tools or dashboards.
• Collaborate with R&D teams to understand workflow needs.
• Document code, workflows, and analysis results clearly.
• Support validation of data-processing workflows.

Minimum Qualifications:

• Must be enrolled in an accredited university or college for at least one semester prior to internship or co-op, and at least one additional semester following internship or co-op.
• Must be pursuing at least a Bachelors degree in Data Science, Computer Science, Biomedical Engineering, Optical Engineering, Applied Mathematics, Statistics, or related fields.
• Academic performance: Minimum cumulative GPA 2.8/4.0
• Demonstrated leadership skills (i.e. extracurricular activities or projects)
• Must be authorized to work in the US on a permanent basis without requiring sponsorship (students on an F1 visa with CPT can be accommodated)
• Ability to commit to a 10-12 week, full time (40 hours per week) summer internship

Preferred Qualifications:

• Proficiency in Python.
• Working knowledge of SQL.
• Familiarity with R.
• Experience with data analytics and ML.
• Understanding of data pipelines.
• Ability to create visualizations.
• AI/ML Skills (Preferred) Experience with ML models.
• Knowledge of clustering, anomaly detection, regression.
• Experience applying ML to scientific datasets.
• Domain Knowledge (Preferred) Familiarity with metrology data is a plus.

Attention: Current Alcon Employee/Contingent Worker

If you are currently an active employee/contingent worker at Alcon, please click the appropriate link below to apply on the Internal Career site.

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EEO Statement:

Alcon is an Equal Opportunity Employer and participates in E-Verify. Alcon takes pride in maintaining an inclusive environment that values different perspectives and our policies are non-discriminatory in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status. Alcon is also committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an email to alcon.recruitment@alcon.com and let us know the nature of your request and your contact information.

Key skills/competency:

AI & Data Analytics Intern Optical Metrology, AI/ML, Python, SQL, R, Data Analytics, Data Processing, Optical Metrology, Medical Devices, Statistical Analysis, Automated Reporting, Machine Learning Models