Job description

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). • 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 (English). • Comfortable presenting complex topics to stakeholders at various organizational levels. • Proven team player that can collaborate across functions and organizations. • Ability to develop influential and collaborative relationships. • High resilience and solution-oriented attitude. • adidas celebrates diversity, supports inclusiveness and encourages individual expression in our workplace. We actively encourage individuals with disabilities to apply and will provide reasonable accommodations throughout the recruitment process. We do not tolerate the harassment or discrimination toward any of our applicants or employees. We are an Equal Opportunity Employer. • adidas offers robust and progressive medical, including HSA (Health Savings Account) with employer funding or FSA (Flexible Spending Account) options, dental, vision, prescription drug coverage, adoption, with surrogate and fertility support, short and long-term disability, and basic life and AD&D insurance. Employees are able to enroll in adidas’ 401k plan and Stock Purchase Plan with employer match. Full-time employees are eligible for education assistance and generous Leave policies including 14 weeks of paid parental leave. • Employees are eligible to earn an annual bonus based on company performance. Employees accrue prorated flexible time off in the amount .4388 hours per day that increases with years of service, twelve paid holidays throughout the calendar year and Service Time Off during milestone years. • At adidas we offer a Hybrid work policy which requires attendance in the office Monday through Thursday, with the flexibility to work remotely on Friday each week. For work requiring a high degree of collaboration or an in-person presentation, in-office attendance is required even on Friday. The working location of this position is Portland, OR. • Though our teammates hail from all corners of the world, our working language is English.

Requirements

Must-haves

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.
Global Data & Analytics (e.g., Data Assets, Data Platforms, Data Governance, Market Teams)
Respective business function (GOPS, Finance, HR, Brand Marketing, Wholesale / Retail)
HR (Senior) Management
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).
Familiarity with modern cloud compute platforms (e.g., Databricks, Snowflake).
Solid understanding of relational databases and NoSQL databases.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningpythonsql

Platform: successfactors
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Parental Leave