AI/ML Data Scientist/Engineer

As a Junior AI/ML Data Scientist at Corning, you will be an integral part of the Enterprise Generative AI platform and AI/ML initiatives. Your role involves 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. Key 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. - Collaborate with software engineers to integrate models into applications and pipelines. - Help document models, assumptions, results, and data pipelines. - Monitor model performance, 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. - Leverage tools such as Databricks and AWS SageMaker to manage data, build models, and deploy solutions. - Collaborate with stakeholders, understanding their needs and translating them into AI/ML solutions. - Continually monitor and evaluate the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance. - Stay abreast of the latest AI/ML trends and technologies, identifying opportunities for innovation and improvement. Qualifications Required: - Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. - 24 years of experience in data science, analytics, or machine learning roles, or equivalent academic and project experience. - Proficiency in Python and familiarity with data science libraries (pandas, NumPy, scikit-learn). - Basic understanding of machine learning algorithms and statistical modeling techniques. - Experience working with SQL and relational or NoSQL databases. - Exposure to cloud or data platforms such as Databricks or AWS. - Familiarity with version control tools such as Git. - Ability to clearly communicate data insights and document work. - Experience working in agile or Scrum-based teams. This job at Corning offers you the opportunity to work on cutting-edge AI/ML projects and be part of a team that is driving innovation in various industries. Join Corning to break through limitations and make a real impact on the world. As a Junior AI/ML Data Scientist at Corning, you will be an integral part of the Enterprise Generative AI platform and AI/ML initiatives. Your role involves 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. Key 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. - Collaborate with software engineers to integrate models into applications and pipelines. - Help document models, assumptions, results, and data pipelines. - Monitor model performance, 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. - Leverage tools such as Databricks and AWS SageMaker to manage data, build models, and deploy solutions. - Collaborate with stakeholders, understanding their needs and translating them into AI/ML solutions. - Continually monitor and evaluate the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance. - Stay abreast of the latest AI/ML trends and technologies, identifying opportunities for innovation and improvement. Qualifications Required: - Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. - 24 years of experience in data science, analytics, or machine learning