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Msc thesis project - improvements in sampling for product qualification using binary data (m/f/d)

Marktheidenfeld
Procter & Gamble
Inserat online seit: Veröffentlicht vor 22 Std.
Beschreibung

From its foundation 185 years ago as a soap and candle start-up, P&G today is a leading consumer goods company. 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. 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.
Bayesian optimization, Network meta-analysis, Gaussian Process Modeling, and Mixed effect modeling, as well machine learning modeling techniques.

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 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; JMP software; SQL and/or Databricks.
Short work experience, internships and studies abroad are also considered as a plus.
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.
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.
To optimally prepare for our online assessment & interviews, make sure you fully understand our assessment process our application process.
Copy of relevant work, internship and volunteering certificates or reference letters
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. Full time
Internships

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

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