AI/ML Data Scientist/Engineer

As a Junior AI/ML Data Scientist at Corning, you will be supporting the Enterprise Generative AI platform and AI/ML initiatives across the company. Your role will involve building, testing, and supporting data science and machine learning solutions 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.
• Collaborate with software engineers to integrate models into applications and pipelines.
• Monitor model performance, troubleshoot, and assist with improvements.
• Build scalable AI/ML models for various use cases such as price elasticity and recommendation systems.
• Leverage tools like Databricks and AWS SageMaker for managing data, building models, and deploying solutions.
• Collaborate with stakeholders to understand their needs and translate them into AI/ML solutions.
• Stay updated on the latest AI/ML trends and technologies for innovation and improvement.

**Qualifications:**

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 24 years of experience in data science, analytics, or machine learning roles.
• Proficiency in Python, data science libraries (pandas, NumPy, scikit-learn), and machine learning algorithms.
• Experience with SQL, relational or NoSQL databases, cloud or data platforms like Databricks or AWS, and version control tools like Git.
• Strong communication skills to convey data insights and document work effectively.
• Familiarity with agile or Scrum-based teams.

**Desired Skills:**

• Exposure to Generative AI models or LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic).
• Familiarity with time-series forecasting methods and vector databases.
• Experience with notebook environments like Jupyter and interest in enterprise AI platforms and scalable solutions. As a Junior AI/ML Data Scientist at Corning, you will be supporting the Enterprise Generative AI platform and AI/ML initiatives across the company. Your role will involve building, testing, and supporting data science and machine learning solutions 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.
• Collaborate with software engineers to integrate models into applications and pipelines.
• Monitor model performance, troubleshoot, and assist with improvements.
• Build scalable AI/ML models for various use cases such as price elasticity and recommendation systems.
• Leverage tools like Databricks and AWS SageMaker for managing data, building models, and deploying solutions.
• Collaborate with stakeholders to understand their needs and translate them into AI/ML solutions.
• Stay updated on the latest AI/ML trends and technologies for innovation and improvement.

**Qualifications:**

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 24 years of experience in data science, analytics, or machine learning roles.
• Proficiency in Python, data science libraries (pandas, NumPy, scikit-learn), and machine learning algorithms.
• Experience with SQL, relational or NoSQL databases, cloud or data platforms like Databricks or AWS, and version control tools like Git.
• Strong communication skills to convey data insights and document work effectively.
• Familiarity with agile or Scrum-based teams.

**Desired Skills:**

• Exposure to Generative AI models or LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic).
• Familiarity with time-series forecasting methods and vector databases.
• Experience with notebook environments like Jupyter and interest in enterprise AI platforms and scalable solutions.