Manufacturing Data Scientist: Analytics, DOE & Dashboards

Corning Incorporated; Reynosa; Presencial; MXN 360.000 - 600.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Benefits above law

Collaborative global environment

Professional development opportunities

Exposure to manufacturing analytics

Impactful data-driven transformation

Descripción de la vacante

Corning Incorporated in Reynosa, Mexico is seeking a Data Analyst to partner with engineering and manufacturing teams to analyze process and quality data, identify opportunities, and support data-driven decisions.

You will use statistics, SQL, Python, and visualization tools to translate complex datasets into actionable insights, develop dashboards, and communicate findings to stakeholders in a global manufacturing environment.

Formación

• Requires a quantitative degree and strong statistics background.
• Experience with data analytics, processing and interpretation of datasets.
• Proficient in SQL and Python for data extraction and analysis.
• Excellent communication with technical stakeholders.

Responsabilidades

• Analyze manufacturing process and quality data to identify trends and opportunities.
• Apply statistical methods including hypothesis testing, SPC, DOE.
• Develop dashboards and reports to support data-driven decisions.
• Collaborate with engineering and manufacturing teams to deliver insights.

Conocimientos

Statistical analysis

Data visualization

Analytical thinking

Problem solving

English communication

Educación

Bachelor's degree in Statistics, Data Science, Mathematics, Computer Science, Industrial Engineering, or related technical field

Herramientas

SQL

Python

Descripción del empleo

Corning Incorporated in Reynosa, Mexico is seeking a Data Analyst to partner with engineering and manufacturing teams to analyze process and quality data, identify opportunities, and support data-driven decisions.

You will use statistics, SQL, Python, and visualization tools to translate complex datasets into actionable insights, develop dashboards, and communicate findings to stakeholders in a global manufacturing environment.