Location: Cologne, on site
Language: German
Our client is a leading company with a presence in all major cities across Germany, offering multiple digital products and services that simplify everyday life for their customers. Experience the fast paced world of e commerce, agile workflows, flat hierarchies, and rapid personal and professional growth.
They are currently seeking a Junior Data Scientist / Machine Learning Engineer passionate about building end to end solutions and driving innovation.
Requirement:
* Strong academic background in fields such as data science, (business) informatics, mathematics, physics, or statistics.
* Initial hands on experience in data science projects, ideally including exposure to ranking and recommendation systems.
* Proficient in the Python data science ecosystem (Pandas, Scikit learn, SciPy) and familiar with deep learning frameworks like PyTorch or TensorFlow.
* A creative and inquisitive mindset for leveraging cutting edge data science algorithms to enhance products.
* Enthusiasm for cross functional collaboration between IT and product management, and active participation in the companys Data Science Community.
* Excellent communication skills in both German and English, written and spoken.
Responsibilities:
* Develop new machine learning services focused on recommendation and ranking systems, information extraction, and predictive analytics, handling everything from concept design and data preparation to model training, evaluation, and deployment readiness.
* Oversee your training experiments using modern MLOps tools like MLFlow to elevate the products performance.
* You collaborate closely with the development team to integrate your models into the product, both technically and content wise, often utilizing cloud platforms such as AWS.
* You stay informed about the latest advancements in machine learning to continuously improve solutions.
* You work within a multidisciplinary team, partnering directly with product managers, developers, and business intelligence experts.
Benefits:
1. Enjoy up to 40 days of paid leave with flexible choices, such as working from home on Fridays or opting for a salary boost.
2. Support for personal growth through dedicated training budgets and consistent performance feedback.
3. Secure a permanent position with competitive pay, bonuses, and benefits such as fitness memberships, childcare support, and company discounts.
4. Benefit from free nationwide public transport and access to company bike leasing programs.
5. Work in a modern office offering complimentary meals, snacks, and ergonomic gear, including a MacBook and