MSc Thesis Project – Sampling Improvements (m/f/d)

- Completed bachelors degree with strong academic results in statistics or equivalent background in a related field - Familiarity with a broad range of statistical methods including Bayesian optimization & other sequential learning techniques - Ability to apply statistical engineering methodologies to define problems, develop experimental plans, model data, extract insights, and scale successful models - Availability for a duration of at least 6 months - Effective collaboration with diverse groups, embracing creativity, innovation, and initiative - Capable of making complex decisions using data and instinct - Strong communication & collaboration skills, ability to explain statistical concepts to non-experts - Proficiency in written and spoken English - Additional skills in coding (Python, R, and/or SAS), foundations of machine learning/artificial intelligence, JMP software, GitHub, SQL and/or Databricks are an advantage - Short work experience, internships, and studies abroad are considered a plus