Data Scientist (Portland, OR, US)

PURPOSE The Data Scientist will develop key data science products, methods, and models across the full analytics lifecycle: from defining the business & data understanding to data preparation, modeling, evaluation and deployment. KEY RESPONSIBILITIES Data Science Lead the development of data science methods, models, and products in support of North America stakeholders. Enhance existing data science methods, models, and products. Continuously improve our methodologies and challenge the status quo, raising the standards for faster delivery. Support improving and automating the data science platform and our machine learning pipeline to facilitate our data science activities and service use cases. Data Science Network and Storytelling Develop and nurture a data science network, both within and outside of adidas, to ensure that best practices and innovations are disseminated across the company. Support presenting and promoting results and insights to adidas colleagues at all levels. Stakeholder Management Manage relationships with key stakeholders, ensuring their views and requirements are captured. Act as the ambassador for your products, showcasing the key functionalities, driving adoption and assuring operational excellence together with IT peers. KEY RELATIONSHIPS Global Data & Analytics (e.g., Data Assets, Data Platforms, Data Governance, Market Teams) Global IT Respective business function (GOPS, Finance, HR, Brand Marketing, Wholesale / Retail) HR (Senior) Management Digital REQUISITE EDUCATION AND EXPERIENCE / MINIMUM QUALIFICATIONS Education & Professional Experience Bachelor or Master’s degree in Data Science, Mathematics, Statistics, or related technical discipline. At least 5-7 years work experience, preferably in a data science or analytics environment. Will accept any suitable combination of education, training or equivalent relevant job experience. Proven track record of working with senior stakeholders. Proficiency in data science methods (including supervised techniques, unsupervised techniques, recommender systems). Proficiency in Python and at least three of the standard data science programming frameworks (e.g., PySpark, Pandas, Numpy, sklearn, lightgbm, Matplotlib, Seaborn, mlflow). <li style="margin-bottom:0.0in;line-height:normal;margin-top:0.0in;margin-rig