AI/ML Data Scientist/Engineer

As a Junior AI/ML Data Scientist at Corning, you will play a vital role in supporting the Enterprise Generative AI platform and AI/ML initiatives across the company. Your responsibilities will include:

• Supporting the development and validation of machine learning and statistical models for business use cases.
• Assisting in building forecasting and predictive models using established techniques and libraries.
• Contributing to Generative AI use cases, including prompt development, evaluation, and basic experimentation with LLMs.
• Supporting Retrieval-Augmented Generation (RAG) workflows, including document ingestion, embeddings, and retrieval.
• Performing data preparation, feature engineering, and exploratory data analysis.
• Collaborating with software engineers to integrate models into applications and pipelines.
• Monitoring model performance, troubleshooting, and making improvements.
• Participating in agile ceremonies such as sprint planning, stand-ups, and retrospectives.
• Building scalable AI/ML models for various use cases like price elasticity and recommendation systems.
• Leveraging tools like Databricks and AWS SageMaker to manage data, build models, and deploy solutions.
• Collaborating with stakeholders to understand their needs and translate them into AI/ML solutions.
• Continually monitoring and evaluating the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance.
• Staying updated on the latest AI/ML trends and technologies to identify opportunities for innovation and improvement.

Qualifications for this role include:

• 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.

Required Skills:

• 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.

Desired Skills:

• Exposure to Generative AI models or LLM APIs (e.g., OpenAI, Azure OpenAI, Anthr) As a Junior AI/ML Data Scientist at Corning, you will play a vital role in supporting the Enterprise Generative AI platform and AI/ML initiatives across the company. Your responsibilities will include:
• Supporting the development and validation of machine learning and statistical models for business use cases.
• Assisting in building forecasting and predictive models using established techniques and libraries.
• Contributing to Generative AI use cases, including prompt development, evaluation, and basic experimentation with LLMs.
• Supporting Retrieval-Augmented Generation (RAG) workflows, including document ingestion, embeddings, and retrieval.
• Performing data preparation, feature engineering, and exploratory data analysis.
• Collaborating with software engineers to integrate models into applications and pipelines.
• Monitoring model performance, troubleshooting, and making improvements.
• Participating in agile ceremonies such as sprint planning, stand-ups, and retrospectives.
• Building scalable AI/ML models for various use cases like price elasticity and recommendation systems.
• Leveraging tools like Databricks and AWS SageMaker to manage data, build models, and deploy solutions.
• Collaborating with stakeholders to understand their needs and translate them into AI/ML solutions.
• Continually monitoring and evaluating the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance.
• Staying updated on the latest AI/ML trends and technologies to identify opportunities for innovation and improvement.

Qualifications for this role include:

• 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.

Required Skills:

• 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.

Desired Skills:

• Exposure to Generative AI models or LLM APIs (e.g., OpenAI, Azure OpenAI, Anthr)