Data Scientist

The Data Scientist develops key data science products, methods and models across the full analytics lifecycle, from defining business and data understanding through data preparation, modelling, evaluation and deployment. The role supports North America stakeholders and sits within the Data team. The position works closely with Global Data & Analytics, Global IT, and business functions such as GOPS, Finance, HR, Brand Marketing and Wholesale/Retail, as well as HR (senior) management and Digital.

• 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 methodologies and challenge the status quo, raising the standards for faster delivery.
• Support the improvement and automation of the data science platform and machine learning pipeline to facilitate data science activities and service use cases.
• Develop and nurture a data science network, both within and outside adidas, to ensure best practices and innovations are disseminated across the company.
• Support presenting and promoting results and insights to adidas colleagues at all levels.
• Manage relationships with key stakeholders, ensuring their views and requirements are captured.
• Act as the ambassador for the products, showcasing key functionalities, driving adoption and assuring operational excellence together with IT peers.

• Bachelor's or Master's degree in Data Science, Mathematics, Statistics or a related technical discipline.
• At least 5-7 years of work experience.
• Any suitable combination of education, training or equivalent relevant job experience will be accepted.
• Proven track record of working with senior stakeholders.
• Proficiency in data science methods, including supervised techniques, unsupervised techniques and 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).
• Familiarity with modern cloud compute platforms (e.g. Databricks, Snowflake).
• Solid understanding of relational databases and NoSQL databases.
• Proficiency in SQL.
• Solid understanding of Machine Learning Operations (MLOps) required to scale and sustain use cases in a large and global corporation.
• Concise written and oral communication skills in English.
• Comfortable presenting complex topics to stakeholders at various organisational levels.
• Proven team player able to collaborate across functions and organisations.
• Ability to develop influential and collaborative relationships.
• High resilience and a solution-oriented attitude.

• Work experience in a data science or analytics environment.

• Hybrid work policy requiring attendance in the office Monday through Thursday, with the flexibility to work remotely on Friday each week.
• In-office attendance is required even on Friday for work requiring a high degree of collaboration or an in-person presentation.

• Robust and progressive medical cover, including HSA (Health Savings Account) with employer funding or FSA (Flexible Spending Account) options.
• Dental, vision and prescription drug coverage.
• Adoption support, including surrogate and fertility support.
• Short and long-term disability cover, plus basic life and AD&D insurance.
• Enrolment in adidas' 401k plan and Stock Purchase Plan with employer match.
• Education assistance for full-time employees.
• Generous leave policies, including 14 weeks of paid parental leave.
• Eligibility to earn an annual bonus based on company performance.
• Prorated flexible time off accruing at 0.4388 hours per day, increasing with years of service.
• Twelve paid holidays throughout the calendar year and Service Time Off during milestone years.

The company believes that embedding diversity, equity and inclusion into its culture and talent processes gives employees a sense of belonging and the brand a real competitive advantage.