Junior AI/ML Data Scientist

About the job

The Junior AI/ML Data Scientist – Generative AI Products is a role supporting Corning’s Enterprise Generative AI platform as well as AI/ML initiatives across the company. This position focuses on building, testing, and supporting data science and machine learning solutions, including forecasting models, analytics workflows, and Generative AI use cases, under the guidance of senior data scientists and engineers. Responsibilities: • Support development and validation of machine learning and statistical models for business use cases • Assist in building forecasting and predictive models using established techniques and libraries • Contribute to Generative AI use cases including prompt development, evaluation, and basic experimentation with LLMs • Support Retrieval-Augmented Generation (RAG) workflows including document ingestion, embeddings, and retrieval • Perform data preparation, feature engineering, and exploratory data analysis • Work with structured and unstructured data from enterprise sources and AI platforms • Collaborate with software engineers to integrate models into applications and pipelines • Help document models, assumptions, results, and data pipelines • Monitor model performance and assist with troubleshooting and improvements • Participate in agile ceremonies including sprint planning, stand-ups, and retrospectives • Build scalable AI/ML models for given use cases, including price elasticity and recommendation systems, ensuring applicability/reusability across multiple business units.

Requirements

• Machine Learning
• Data Analysis
• Python
• SQL

Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering
• 2–4 years of experience

Preferred Technologies

• Machine Learning
• Data Analysis
• Python
• SQL

About the company

Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what’s possible.