Job Location
Kronberg
Job Description
Are you passionate about an exciting career in R&D? Are you ready to get hands on experience with rich Data base of R&D functions? If you relish a culture in which your development is key and you feel a hunger to learn, a dedication to lead, and a passion to win – this position is for you!
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!
YOUR ROLE
As Intern for Data Science, ML and AI in P&G’s German Innovation Center (GIC), you build and optimize Data models and Algorithms. You will use ML and AI techniques in combination with R&D Data and models to provide meaningful contributions and impactful results.
Job Qualifications
YOUR PROFILE
WHAT WE OFFER
APPLICATION
To optimally prepare for our online assessment & interviews, make sure you fully understand our assessment process our application process.
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. 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.
Job Schedule
Full time
Job Number
R000110740
Job Segmentation
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