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Johnson & Johnson Innovative Medicine in Schaffhausen, Switzerland, invites an intern/co-op in Data Science to join cross-functional teams turning manufacturing, lab, and equipment data into actionable insights. You will build dashboards, run exploratory analyses, and help implement predictive models to improve process performance.
The role requires a Master’s in quantitative field, up to 2 years of relevant experience, and strong Python/SQL skills with data visualization proficiency.
At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com.
As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.
Job Function:
Career Programs
Job Sub Function:
Non-LDP Intern/Co-Op
Job Category:
Career Program
All Job Posting Locations:
Schaffhausen, Switzerland
Job Description:
What you’ll do:
Support cross-functional teams to turn manufacturing, lab and equipment data into actionable insights that improve efficiency, yield, reduce variability and accelerate investigations.
High level of entrepreneurship and independence — proactively driving new ideas, challenging the status quo, and leading improvement projects from concept through implementation.
Build, validate and operationalize exploratory analyses, dashboards and pilot predictive models for processes, equipment reliability and quality signals.
Help design and analyze experiments and support statistical process control and capability studies.
Implement and maintain fit-for-purpose data pipelines.
Contribute to model governance, documentation, validation activities and data integrity practices consistent with GMP/GxP requirements.
Participate in Kaizen/Lean/Six Sigma initiatives and support root-cause investigations with reproducible analyses.
Communicate results clearly to stakeholders with transparent documentation and pragmatic recommendations.
Learn and follow site safety, quality and confidentiality standards at all times.
What you’ll bring:
Required
Master’s in Data Science, Computer Science, Statistics, Chemical/Bioprocess Engineering, Biotechnology or related quantitative discipline
High academic achievement as proven by overall performance in university
Up to 2 years of relevant experience (including internships or academic projects) applying data analytics or software development.
Hands-on experience with Python; working knowledge of SQL.
Practical experience with visualization tools (Power BI, Tableau, plotly, matplotlib) and reproducible notebooks.
Strong analytical thinking, attention to detail and curiosity about process and product performance.
Clear written and verbal communication skills and ability to work collaboratively across functions.
Required Skills:
Preferred Skills: