COMPANY DESCRIPTION
About the DOUGLAS Group
The DOUGLAS Group, with its commercial brands DOUGLAS, NOCIBÉ, Parfumdreams and Niche Beauty, is the number one omnichannel premium beauty destination in Europe. The DOUGLAS Group is inspiring customers to live their own kind of beauty by offering a unique assortment online and in around 1,900 stores. With unparalleled size and access to customers, the DOUGLAS Group is the partner of choice for brands and offers a premium range of selective and exclusive brands as well as own corporate brands. The assortment includes fragrances, color cosmetics, skin care, hair care, accessories as well as beauty services. Strengthening its successful omnichannel positioning while consistently developing superior customer experience is at the heart of the DOUGLAS Group strategy “Let it Bloom”. The winning business model is underpinned by the Group’s omnichannel proposition, leading brands, and data capabilities. In the financial year 2023/24, the DOUGLAS Group generated sales of 4.45 billion euros and employed around 19,200 people across Europe. It was named the World’s Top Company for Women in 2025 among all retail and wholesale companies by Forbes. The DOUGLAS Group (Douglas AG) is listed at the Frankfurt Stock Exchange.
For further information please visit the DOUGLAS Group Website.
TASKS WITH IMPACT
* Contribute to the Douglas Analytics Strategy by developing and defining requirements for the development environment for advanced analytics and machine learning.
* Develop and implement machine learning models, including modern algorithms such as generative AI, in close collaboration with data scientists and engineers.
* Take ownership of machine learning use cases at Douglas, with responsibility for the development, optimization, and continuous improvement of the models.
* Support the scaling and operationalization of machine learning models to ensure they meet operational and business requirements in production environments.
* Stay updated on the latest developments in machine learning and big data engineering, and apply new techniques and tools to improve workflows and processes.
YOUR SKILLS
* A completed degree in Computer Science, Machine Learning, or a related field.
* Several years of experience in machine learning engineering, data engineering, or a similar role focused on the development and deployment of large-scale machine learning models.
* Strong ability to develop and tailor machine learning models to business requirements.
* Extensive knowledge of machine learning frameworks and programming languages, particularly Python.
* Deep understanding of data engineering tools and technologies, including big data frameworks.
* Experience working with cloud platforms.
YOUR BENEFITS
Your personal development: we want you to grow with us. Become part of our mentoring program, use our e-learning platforms and benefit from many other individual development opportunities.
️ Open feedback culture: half-yearly meetings & performance reviews (#DOUGLASDialogue)
30 days of vacation per year
Would you like a hybrid working model? We offer a balance between mobile working and office days in a collaborative environment. (approx. 8 days/month)
Cherry on top: You get our employee discount both online and in-store. On top of that, you get further discount opportunities thanks to our corporate benefits.
???? In-house canteen & bistro, as well as free drinks
A positive and motivating environment & celebrating successes at regular company events such as DOClub, summer party, Women's Day, etc
DO YOU RECOGNIZE YOURSELF?
Then become part of our international company and apply, stating your salary expectations and possible starting date.
As an international employer, we stand for equal opportunities and diversity. We therefore welcome applications from mothers, fathers, people with disabilities and people from the LGBTQIA+ community. Please let us know if, for example, we should use a gender-neutral pronoun, if you need barrier-free access to our offices or if we should allow more time for the application process.
We look forward to hearing from you!
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