Salary: 30.000 - 30.000 € per year Requirements: 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. Responsibilities: Evaluating the foundations of our qualification protocols (i.e. Binomial SPRT) & comparing vs. the state-of-the-art. Analyzing historical data from qualification events & study opportunities to leverage prior experiences, e.g. accounting for factors or events influencing total probabilities. Performing proper simulations in various scenarios to estimate rate of attribute defects. Initiate a database that enables historical trend analyses. Evaluate possible applications of ML approaches (e.g. Genetic Algorithms). Make progress in the subject and integrate the learning experience to make a compelling case for the organization to implement any applicable improvement. Technologies: Cloud Databricks GitHub Machine Learning Python SAS SOAP SQL HTTP Network More: From its foundation 185 years ago as a soap and candle start-up, we at P&G today are a leading consumer goods company. We are home to iconic, trusted brands that touch 5 billion consumers worldwide and make life a little bit easier in small but meaningful ways. Our people are our greatest asset: with our philosophy of promotion from within, we place strong emphasis on employee development and are committed to finding and fostering world-class talent. Learn from our inspiring leaders, shape our supportive and welcoming culture, and place your personal development at the core of your work! last updated 5 week of 2026