Manufacturing Data Analysis Intern, Monterrey, México at Fictiv

Fictiv is seeking a Manufacturing Data Analysis Intern to analyze data related to manufacturing processes, raw materials, and costs. This role involves collaboration with the sourcing department to align data-driven insights with procurement strategies and supplier performance evaluations. The intern will report onsite to the Manufacturing Engineer in Santa Catarina, México.

Role involves:

• Collecting, organizing, and analyzing data from manufacturing processes, raw material usage, and production costs.
• Developing visualizations and reports to communicate key findings and trends to cross-functional teams.
• Identifying patterns and correlations that can uncover opportunities for cost reduction, process optimization, and revenue growth.
• Collaborating with the sales and operations teams to align findings with business strategies.
• Partnering with the sourcing department to evaluate supplier performance, analyze procurement costs, and support strategic sourcing decisions.
• Develop predictive models to anticipate market demands and improve resource allocation.
• Present actionable recommendations to stakeholders based on data analysis.

Requirements:

• Currently pursuing or recently completed a degree in Data Science, Industrial Engineering, Manufacturing, Business Analytics, or a related field.
• Strong analytical skills with proficiency in data analysis tools such as Excel, Python, R, or similar.
• Experience with data visualization tools like Tableau, Power BI, or equivalent.
• Understanding of manufacturing processes and cost structures and sourcing principles is a plus.
• Strong communication and presentation skills in both Spanish and Business English.
• Self-motivated, with the ability to work both independently and in a team environment.

What Fictiv offers:

• Hands-on experience in the digital manufacturing industry.
• Mentorship and professional development opportunities.
• Flexible work hours to accommodate your academic schedule.
• Potential for a full-time role based on performance.