Data Scientist AI / Machine Learning

Job Title: Data Scientist (Machine Learning)

Founded in 1920, Eastman is a global specialty materials company that produces a broad range of products found in items people use every day. With the purpose of enhancing the quality of life in a material way, Eastman works with customers to deliver innovative products and solutions while maintaining a commitment to safety and sustainability. The company’s innovation-driven growth model takes advantage of world-class technology platforms, deep customer engagement, and differentiated application development to grow its leading positions in attractive end markets such as transportation, building and construction, and consumables. As a globally inclusive company, Eastman employs approximately 13,000 people around the world and serves customers in more than 100 countries. The company had 2025 revenue of approximately $8.8 billion and is headquartered in Kingsport, Tennessee, USA. For more information, visit www.eastman.com.

Responsibilities

Data Scientists at Eastman provide actionable insights using advanced analytics to help the company make better and faster decisions. Our centralized Data & Analytics organization includes specialized groups in Applied Statistics, AI/Machine Learning, Operations Research, and Generative AI.

As an early-career Data Scientist in AI/ML, you will apply engineering or scientific domain knowledge, machine learning, statistical modeling, and software-development practices to solve meaningful manufacturing, R&D, and business problems. You will contribute to the design, development, validation, and operationalization of predictive and prescriptive models that support process optimization, product development, forecasting, and other business decisions. You will own defined technical workstreams and collaborate closely with experienced data scientists, engineers, and platform partners on complex technical, production, security, and governance considerations.

This role is well suited for a developing data scientist who has a strong technical foundation and is ready to build broader experience in applied machine learning, cloud-based deployment, and cross-functional delivery. You will work independently on defined project components while collaborating with senior technical team members and platform partners on complex architecture, production, security, and governance decisions.

• Partner with manufacturing, R&D, and business stakeholders to understand problems, evaluate whether machine learning is an appropriate solution, and support the development of practical project plans.
• Design, develop, validate, and maintain machine learning models using Python for applications such as manufacturing process optimization, product and formulation development, predictive analytics, demand forecasting, and computer vision.
• Prepare models and supporting code for production use within Eastman’s enterprise platforms, including Databricks and Azure ML, in collaboration with ML engineering, cloud, infrastructure, and cybersecurity partners as appropriate.
• Contribute to the development of reliable ML workflows, including data preparation, model training, evaluation, version control, documentation, logging, and monitoring.
• Develop scalable, modular, and well-documented Python code using established team standards and MLOps practices.
• Participate actively in code reviews, technical design discussions, testing, and knowledge sharing to improve the quality, reliability, and maintainability of team deliverables.
• Communicate model methodology, performance, limitations, recommendations, and business implications clearly to technical and nontechnical stakeholders through documentation, visualizations, and presentations.
• Collaborate with chemical engineers, chemists, process and control engineers, statisticians, data engineers, and business intelligence professionals to integrate ML solutions into operational and business processes.
• Follow established ML governance, security, data-management, and Responsible AI processes, including supporting required risk assessments and review activities.

Qualifications

Required:

• Master’s, or doctoral degree completed within the last two years, or expected by the start date, in Chemical Engineering, Industrial Engineering, Mechanical Engineering, Materials Science, Chemistry, Process Control, Computer Science, Data Science, Statistics, Operations Research, or another related technical discipline.
• Demonstrated experience applying data analysis, statistics, machine learning, optimization, or software development to real-world technical problems through coursework, research, design projects, internships, co-ops, or early-career employment.
• Hands-on Python experience for data analysis, modeling, automation, or application development.
• Strong quantitative problem-solving skills and the ability to understand a technical problem, assess available data, apply an appropriate analytical approach, and interpret results in the context of the underlying process.
• Ability to communicate clearly, collaborate effectively, and learn quickly in a cross-functional technical environment.

Preferred:

• Educational background or practical experience in chemical manufacturing, process engineering, process control, product development, formulation, materials science, plant operations, utilities, or other industrial environments.
• Experience applying machine learning, advanced analytics, optimization, or statistical methods to engineering, manufacturing, R&D, reliability, quality, supply-chain, or operational problems.
• Experience with time-series data, sensor or historian data, process data, forecasting, computer vision, optimization, hybrid modeling, or physics-informed machine learning.
• Experience developing, testing, deploying, or supporting analytics or ML solutions in a production or operational setting.
• Familiarity with Databricks, Azure ML, MLflow, Docker, cloud platforms, SQL, APIs, data warehousing, or application-development frameworks.
• Experience using experimental design, process understanding, first-principles engineering knowledge, or subject-matter expertise to improve model design, validation, and interpretation.
• Experience working in an iterative or Agile project-delivery environment.

Eastman will not accept applicants for this offered position who require visa sponsorship, including those whose status is F-1 visa OPT who subsequently would require ongoing visa sponsorship.

Eastman is an equal opportunity employer and is committed to creating a highly engaged workforce, where everyone can contribute to their fullest potential each day.