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

- You have a completed bachelors degree, and strong academic results in statistics or have equivalent background in a related field, familiar with a broad range of statistical methods (e.g. foundation in Bayesian optimization & other sequential learning techniques), along with passion for applying statistical skills to partner disciplines in ways that accelerate business processes. - You have the ability to apply statistical engineering or similar methodologies to (1) define problems and provide structure and metrics for solving them, (2) develop experimental plans, (3) model data, (4) extract insights, and (5) scale successful models for broader use. - You are available for a duration of at least 6 months. - You work effectively with diverse groups of people by embracing creativity, innovation, and initiative. - You are skilled to make complex decisions using all the data available but confident to use your gut feeling and instinct. - You have strong communication & collaboration skills, with an ability to explain sophisticated statistical concepts to non-experts and maintain relationships both within our immediate team and several partner organizations. - You can speak and write proficiently in English. - Additional awareness of any of the following would be an advantage: coding skills in Python, R, and/or SAS & ability to connect to cloud databases and write queries to download data; Foundations of machine learning / artificial intelligence; JMP software; GitHub; SQL and/or Databricks. - Short work experience, internships, and studies abroad are also considered a plus.