MSc Thesis Project - Improvements in Sampling for product qualification using binary data (m/f/d)

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Job Description

YOUR FUTURE EMPLOYER

From its foundation 185 years ago as a soap and candle start-up, P&G today is 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!

Are you eager to lead exciting projects and have a meaningful impact with your ideas? At P&G, our Engineering team delivers the technologies that make product innovation possible. Together, we create irresistible, meaningful, and sustainable experiences for our consumers. Every change we make in our production systems meet rigorous qualification standards with solid foundation in statistics, ensuring the quality of our products.

From Day 1 , you will be exploring & developing alternative, more affordable sampling techniques & tools with equivalent statistical confidence by

• 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.

We believe expertise or interest in developing in one or more of the following techniques may be relevant: Bayesian optimization, Network meta-analysis, Gaussian Process Modeling, and Mixed effect modeling, as well machine learning modeling techniques.

Job Qualifications

YOUR PROFILE

• 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 providing 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.

WHAT WE OFFER

• Exciting work and responsibility from Day 1.
• A competitive internship salary (monthly starting salary 2,500€).
• Wide range of social benefits: e.g., flexible work environment, regular intern social connects, a buddy program, campus services such as fitness center and canteen etc.
• A customized personal development plan including relevant coaching, mentorship, training-on-the-job, and a large portfolio of individual upskilling opportunities.
• The experience to be an integral part of our multi-functional teams of passionate and inspiring people with flat hierarchies to get to know the unique P&G culture.
• The chance to receive a full-time employment offer to start after your studies with diverse career perspectives including new job assignments every 2-3 years to gain experience in different areas and the opportunity to work abroad.
• Opportunity to engage in our various employee programs: WeBelong Team & New Hire Network activities, GABLE Network & other affinity groups, Inspirational Leadership Events, Sports groups for running & football etc.
• Collaborate & manage multi-functional teams with international spirit, work with colleagues across regions and all levels.

APPLICATION

To optimally prepare for our online assessment & interviews, make sure you fully understand our assessment process our application process.

• CV as a separate document
• Cover letter (optional)
• Copy of university diploma (if applicable) and transcript
• Copy of relevant work, internship and volunteering certificates or reference letters

Please upload all documents in the "CV/Resume" field. Incomplete applications may lead to delays in the recruitment process.

At P&G #weseeequal

We are an equal opportunity employer and value diversity at our company. At P&G, we strive to build a culture where everyone feels welcome, included, and able to bring their full selves to work.

We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process. Please click here if you require an accommodation during the application process and please make sure to wait to hear back from us regarding your accommodation before proceeding with the online assessment. We thank you in advance for your patience.

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