Data Scientist - Global Ops (M/F/D)

adidas is on a mission to be the best sports brand in the world. To successfully work towards this goal, a business needs the right insights at hand at the right time. This is where data and advanced analytics play a pivotal part. Data and advanced analytics at adidas are more than just a tech service, but a value-oriented business function that actively and directly impacts adidas’ P&L.

 

The Global Operations (GOPS) Advanced Analytics (AA) team is a core team of analytical professionals working on GOPS topics ranging from inventory management, production strategies, transportation optimization, and various other logistics and supply chain use cases. GOPS AA is looking for a Data Scientist to strengthen the team. As a Data Scientist within the GOPS AA team, you will work hand in hand with the Global Operations organization on strategically relevant use cases that have the potential to deliver substantial, measurable business value. You will be involved in the full analytics lifecycle: from business and data understanding to data preparation, modeling, evaluation, and deployment, and work closely with other stakeholder groups.

  

KEY RESPONSIBILITIES

  • Support the development of data science methods for specific GOPS use cases
  • Continuously improve our methodologies and challenge the status quo, raising the standards for better delivery
  • Support improving and automating the data science platform and our machine learning pipelines to facilitate our data science activities and service use cases
  • Develop and nurture a data science network, both within and outside of adidas, to ensure that best practices and innovations are shared and applied across the company
  • Support presenting and promoting results and insights to adidas colleagues at all levels   
  • Together with our Product Owners, manage the relationships with a specific GOPS project team, ensuring their views and requirements are captured
  • Be an analytical sparring partner for the business
  • Act as the ambassador for your use case(s), showcasing the key functionalities, driving adoption, and assuring operational excellence together with IT peers
     

KEY RELATIONSHIPS

  • Various GOPS stakeholders
  • Other teams within Data & Analytics (e.g., data assets, data platforms, data governance, market teams)


EXPERIENCE REQUIRED

  • Proficient spoken and written command of English
  • +4 years of work experience, preferably in a data science or analytics 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)
  • Expertise in open-source unified analytics engine for large-scale data processing (PySpark)
  • Solid understanding of relational databases and NoSQL databases. Experience working with Databricks (preferred)
  • Solid knowledge of Machine Learning Operations (MLOps)
  • Familiarity with agile development methodology
  • Analytics/data science experience in supply chain, logistics, and transportation is seen as a plus
  • Comfortable in presenting complex topics to stakeholders at various organizational levels
  • A great sense of humor :)

 

WHAT ARE WE OFFERING?

  • 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

 

» Please apply with your English Cv «

adidas celebrates diversity, supports inclusiveness and encourages individual expression in our workplace. We do not tolerate the harassment or discrimination toward any of our applicants or employees. We are an Equal Opportunity Employer.

Job Title:  Data Scientist - Global Ops (M/F/D)

Brand:  adidas
Location:  Porto
TEAM:  Information Technology
State:  13
Country/Region:  PT
Contract Type:  Full time
Number:  491217
Date:  Nov 14, 2022