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À propos
Join Corning, 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. With our people, they break through limitations and expectations not once in a career, but every day. They help move our company, and the world, forward. As a leading developer, manufacturer, and global supplier of scientific laboratory products for 100 years, Corning's Life Sciences segment collaborates with researchers seeking new approaches to increase efficiencies, reduce costs, and compress timelines in the drug discovery process. Using unique expertise in the fields of materials science, surface science, optics, biochemistry, and biology, the segment provides innovative solutions that improve productivity and enable breakthrough discoveries. Scope of Position: You will be joining the Data Science and Innovation Team for the Corning Life Science division. Depending on your skills and interests, you will contribute to a variety of projects, including but not limited to revenue forecasting, manufacturing simulation and optimization, and applications of generative AI. Day to Day Responsibilities: Identify, retrieve, clean, and validate data across multiple sources using SQL, Python, and Spark to ensure data quality and usability Apply advanced analytics, machine learning, and AI techniques to understand, predict, and optimize key business drivers and opportunities Build, deploy, and maintain production-ready models using Databricks, MLOps practices, and GitLab CI/CD Create clear model documentation and communicate results and insights to both technical and non-technical stakeholders Participate in the Corning-wide data community Required Education and Years of Experience: Bachelor's or Master's degree in Data Science, Computer Science, Operations Research, or a related quantitative field Minimum of 3 years of professional experience in data science or related roles Required Skills: Proficiency in SQL, Python, Spark Proficiency in data preprocessing, feature engineering, and exploratory data analysis Experience applying common machine learning techniques (e.g., regression, classification, tree-based models), with an understanding of key parameters and trade-offs Experience with MLOps fundamentals including experiment tracking, model versioning, validation, and monitoring Ability to translate business problems into analytical approaches and communicate results clearly Desired Skills: Experience with Databricks is a plus Experience building lightweight machine learning applications (e.g., Streamlit) that enable business users to explore, interact with, or apply model results Experience with operations research techniques Experience building generative AI applications This position does not support immigration sponsorship. The range for this position is $108,951.00 - $149,808.00 assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. Pay Grade: Grade C Employee Referral Amount: $1,500.00 USD Nearest Major Market: Boston
Compétences linguistiques
- English
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