Date: Aug 22, 2025
Location: Austin, TX, US, 78726 Keller, TX, US, 76248
Company: Corning
Requisition Number: 70323

REQUIRED QUALIFICATIONS

• Bachelor’s in Data Science, Computer Science, Engineering, Statistics, or a related field.
• 5+ years of experience in data science, analytics, or a related field, preferably in a manufacturing or industrial setting.
• Proficiency in Python, R, SQL, and experience with big data platforms (e.g., Databricks, Spark, Hadoop).
• Strong foundation in statistical modeling, machine learning, and data mining techniques.
• Experience with cloud platforms (e.g., Azure, AWS, GCP) and modern data architectures.
• Advanced data visualization skills using Power BI, Tableau, or similar tools.
• Excellent communication and leadership skills with the ability to influence at all levels of the organization.

DESIRED QUALIFICATIONS

• Master’s or Ph.D. in Data Science, Computer Science, Engineering, Statistics, or a related field.
• Experience with manufacturing systems (MES, ERP) and industrial data platforms (e.g., OSI PI).
• Familiarity with MLOps practices and tools for model deployment and monitoring.
• Bilingual (English/Spanish) and experience working with international or cross-cultural teams.
• Professional certifications in Data Science, Machine Learning, or related fields.

ROLE PURPOSE

The Senior Process Data Scientist will lead the development and deployment of advanced analytics solutions to drive strategic decision-making and operational excellence across the organization through process improvement. This role will focus on leveraging machine learning, statistical modeling, and big data technologies to uncover insights, optimize processes, and support the digital transformation journey, including Manufacturing 4.0 initiatives.

KEY RESPONSIBILITIES

• Design and implement scalable data science solutions for complex business problems across manufacturing, engineering, and operations.
• Lead cross-functional analytics projects from ideation to deployment, ensuring alignment with business goals.
• Develop predictive and prescriptive models using machine learning, deep learning, and statistical techniques.
• Architect and maintain robust data pipelines and analytical frameworks in collaboration with data engineering and IT teams.
• Mentor junior data scientists and analysts, fostering a culture of continuous learning and innovation.
• Partner with stakeholders to translate business needs into data-driven strategies and actionable insights.
• Create compelling visualizations and dashboards using tools like Power BI or Tableau to communicate findings effectively.
• Serve as a subject matter expert in data science, guiding best practices in data governance, model validation, and ethical AI.
• Contribute to the advancement of Manufacturing 4.0 by integrating AI/ML into process optimization and automation initiatives.