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 as 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 Support Machine Learning Python SAS SOAP SQL HTTP Network More: At P&G, we are a leading consumer goods company with a history of 185 years, starting as a soap and candle start-up. Our iconic brands impact 5 billion consumers globally by making life easier in meaningful ways. We prioritize our people, emphasizing internal promotion and development while fostering a culture of support and collaboration. Our Engineering team focuses on product innovation and sustainability while you contribute from day one. We offer a competitive internship salary, a flexible work environment, social benefits, and a personalized development plan. Join us to be part of a passionate multi-functional team and gain valuable experience with opportunities for future employment. last updated 5 week of 2026