Key Responsibilities: • Assist in collecting and analyzing data related to materials, production processes, and industrial trends. • Support the team in optimizing material selection and predicting trends using statistical analysis and machine learning. • Contribute to process improvement initiatives by performing data analysis to identify bottlenecks and inefficiencies. • Participate in sustainability analysis efforts to measure the environmental impact of materials and suggest improvements. • Help maintain databases and develop dashboards to visualize KPIs for the CMF team. • Learn to use predictive modeling to forecast customer preferences and assist in test protocol development. • Support R&D with the statistical design of experiments under the guidance of senior team members. • Participate in training and professional development opportunities to enhance skills and knowledge in data science and its applications in CMF engineering. Qualifications: • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field, master is a plus • Candidates with a proficient level of both written and spoken English • • Strong understanding of statistical analysis, predictive modeling, and machine learning algorithms. • Proficiency with data science tools and programming languages such as Python, R, SQL, or similar. • Familiarity with data visualization tools (e.g., Tableau, Power BI). • Excellent problem-solving skills and attention to detail. • Ability to work collaboratively in a team environment. • Strong communication skills, both verbal and written. • Curiosity and eagerness to learn about CMF processes and the intersection of data science with product design. • Prior internship or project experience in data analysis is a plus, but not required.