Data Scientist (M/F/D)

Job description

The Data & Analytics function will include a Wholesale Advanced Analytics team, which will work hand in hand with the Wholesale organization on strategically relevant use cases that have the potential to deliver substantial value and redefine the way that adidas works with its wholesale business partners.

Data Scientists in the Wholesale Advanced Analytics team will support the development of data science methods for specific use cases across the entire analytics lifecycle: from business and data understanding to data preparation, modeling, evaluation, and deployment.

Key Responsibilities
  • Support the development of data science methods for specific Wholesale use cases
  • Support improving and automating the data science platform and our machine learning pipeline to facilitate our data science activities and service use cases
  • Support presenting and promoting results and insights to adidas colleagues at all levels
  • Partly manage the relationships with the Wholesale project team, ensuring their views and requirements are captured
  • Act as the ambassador for your use case, showcasing the key functionalities, driving adoption, and assuring operational excellence together with IT peers
Experience Required
  • Proficient spoken and written command of English
  • +4 years of work experience, preferably in a data science environment
  • Experience in developing and running simulation, optimization, and what-if scenario planning tools to support decision making
  • Proficiency in at least two of the standard data science programming languages (e.g., Python, R, Java, Scala, Octave)
  • Understanding of relational databases and NoSQL databases. Experience working with Databricks (preferred)
  • Expertise in open-source unified analytics engine for large-scale data processing (PySpark)
  • Basic knowledge of Machine Learning Operations (MLOps)
  • Competitive salary, bonus, and benefits
  • Hybrid work policy and flexible working hours
  • Sports and work-life balance incentives
  • Upskilling and internal growth (local and international)
  • International and diverse work environment
  • State-of-art office space and conditions
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