Material Qualification Analytics Intern

Key Responsibilities:

• Develop and implement data science tools to streamline global material qualification processes.
• Collaborate with internal stakeholders to identify and prioritize data science solutions that enhance material implementation efficiency.
• Support strategic projects related to Material Qualification.
• Utilize data-driven decision-making to provide timely recommendations for prioritization and acceleration of material implementations.
• Apply agile principles to simplify processes and increase organizational capacity.

Technical and Functional Expertise:

• Strong problem-solving skills with the ability to analyze unstructured data and align team objectives.
• Proficiency in programming languages such as C , R, and Python.
• Understanding of project sprint methodologies and experience in translating business requirements into technical solutions.

Leadership:

• Demonstrated ability to lead cross-functional projects in a matrix environment.
• Strong communication skills, capable of aligning teams and presenting project updates to various stakeholders.
• Experience in managing change and influencing cross-functional group alignment.

Decision-Making and Autonomy:

• Full accountability for developing and integrating data science tools into the material implementation process.
• Collaborate with line management to align decisions and changes beyond the approved scope.

Interaction:

• Partner with cross-functional teams including quality, procurement, product, and regulatory experts to identify team needs.
• Collaborate across functional areas and manufacturing sites as needed, working independently with guidance from the line manager.

Innovation:

• Explore off-the-shelf data science solutions to expedite Material Qualification efforts.
• Develop in-house tools for enterprise-wide deployment and maximum value capture.

Complexity:

• Demonstrate initiative, sound judgment, and the ability to manage multiple projects with competing deadlines.
• Possess strong time management and organizational skills to handle complex tasks across diverse business environments.

Education and Experience:

• Currently enrolled in a data science, computer science, or STEM degree program (Bachelor of Science).
• Completion of at least two years of study in the field.