Are you passionate about turning data into actionable insights and helping
manufacturing teams make better decisions?

Join a global organization where your expertise in statistics, analytics, and
data visualization can directly contribute to improving manufacturing processes
and performance.

What is your role?

As a Data Analyst, you will partner closely with engineering and manufacturing
teams to analyze process and quality data, identify opportunities for
improvement, and support data-driven decision-making. You will use statistical
analysis, SQL, Python, and visualization tools to understand process performance
and translate complex datasets into clear, actionable insights. This role is
adecuado for someone who enjoys solving problems independently and working directly
with technical stakeholders in a manufacturing environment.

Major responsibilities and tasks of the position:

* Analyze manufacturing, process, and quality data to identify trends,
variation, performance issues, and improvement opportunities.
* Apply statistical methods such as hypothesis testing,



Statistical Process
Control (SPC), process capability analysis, and Design of Experiments (DOE).
* Use SQL and Python to extract, prepare, analyze, and visualize data from
multiple sources.
* Develop dashboards, reports, and visualizations that help engineering and
manufacturing teams make data-driven decisions.

What do you need to have?

* Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science,
Industrial Engineering, or a related technical field.
* Approximately 3+ years of relevant experience in data analytics, statistical
analysis, process analytics, or a related field.Strong knowledge of
statistics and demonstrated ability to analyze and interpret datasets.
* Strong experience with SQL and/or Python for data analysis.Ability to
independently investigate data, identify meaningful insights, and communicate
recommendations to stakeholders.
* Strong attention to detail, analytica

📌 Data Analyst (México)
🏢 Corning
📍 México