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

- 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 models - Minimum availability of 6 months - Effective teamwork and collaboration with diverse groups - Ability to make complex decisions using data and intuition - Strong communication skills, able to explain statistical concepts to non-experts - Proficient in spoken and written English - Awareness of coding skills in Python, R, and/or SAS; ability to connect to cloud databases and write queries; foundations of machine learning; familiarity with JMP software, GitHub, SQL, and/or Databricks is a plus - Short work experience, internships, and studies abroad are advantageous