Intern Data Science - Future Talent Program

Collaborate with senior data scientists to understand business challenges and analytical requirements.

Support data collection, data cleaning, exploratory data analysis, and interpretation of results.

Generate insightful data visualizations and communicate findings to project stakeholders.

Assist in machine learning model development workflows, including feature engineering, model selection, and validation activities.

Document analytical approaches, findings, and processes to enable knowledge sharing and reproducibility.

Contribute to advanced analytics projects focused on Supply Chain and Manufacturing optimization.

Stay informed about emerging trends and technologies in data science, machine learning, and artificial intelligence.

Work collaboratively with business and technical stakeholders to deliver measurable business impact.

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutrition, and branded generic medicines. Through our innovative solutions, we are committed to improving the health and well-being of people around the world.

The central Advanced Analytics team at EPD's headquarters in Basel helps define and lead the transformation toward becoming a global, data-driven organization through the use of advanced technologies including Machine Learning, Deep Learning, Generative AI, and Computer Vision.

The team works closely with the EPD Senior Leadership Team and plays a key role in driving sustainable business growth and operational excellence.

• Currently pursuing a Master's degree in Applied Mathematics, Computer Science, Engineering, Applied Statistics, or a related field.

• Solid experience applying data science methodologies to solve business problems.

• Knowledge of data mining, statistical modeling, predictive analytics, and machine learning techniques.

• Programming experience in Python or R; knowledge of object-oriented programming languages such as Java, C++, or C is considered an advantage.

• Understanding of machine learning deployment concepts and software engineering best practices.

• Experience with testing frameworks and analytical libraries.

• Knowledge of cloud-based data science environments such as AWS or SageMaker is a plus.

• Strong analytical thinking, problem-solving skills, and ability to work in international environments.

• Excellent communication skills and ability to present complex concepts clearly.

• Fluent English language skills; additional languages are an advantage.