Siegwerk is one of the world’s leading suppliers of Printing Inks and sustainable packaging solutions. A career here will give you significant flexibility and support in a company focused on making a positive impact in the world. Siegwerk is poised to disrupt the global packaging industry; changing the way packaging is produced and consumed for the benefit of us all. At Siegwerk, you will have everything you need to help make that change.
Join us, let’s Do it. With Heart.
Location: Alfred-Keller-Straße 55, 53721 Siegburg
Apply now!
Our benefits - What we offer You:
Your Tasks - What You can expect as Working Student Machine Learning (f/m/d)?
After having received a training on an OCR tool (Optical Character Recognition), you will be supporting a global roll-out project for digitizing the order process by training and monitoring the tool and being responsible for 1st level customer support.
You will work closely with the international team in adapting the roll-out to local requirements, performing root cause analysis, investigation, and documentation.
You will engage with key user/customer trainings and onboardings.
You will be working together with key users and the Product Manager Digital Customer Platform to conceptualize and formulate new requirements.
You will perform simple (data) bug fixing, small development tasks, and monitor stuck orders.
Your Profile - What do You bring as Working Student Machine Learning (f/m/d)?
You have an advanced Bachelor’s or studying in Master's studies in computer science, software engineering,
First experience with ML/neuronal networks is a plus, but not a must.
You are interested in latest technology within the digital market to maximize the value of our platform and to enhance the customer experience.
You are enthusiastic, have a hands-on mentality and are a strong team player
Business fluent English, German skills are a plus.
Are you interested?
Should you have any further questions, Daniel Krause looks forward to your call! You can reach him via phone 02241 304 204 as well as via LinkedIn.
Job-ID: 25742
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