Nike is looking to solve complex problems across the apparel and footwear product lifecycle by leveraging data-driven insights and AI to inform and optimize all stages of merchandising and product creation
Requirements
PhD in Data Science, Applied Statistics or related field
Strong statistical and mathematic foundation
Extensive experience with cloud tools for data science, machine learning and modeling, and visualization e.g., PySpark, Databricks, MLFlow, Jupyter Notebooks, RStudio, pandas, SageMaker, Tableau, PowerBI
Expertise in languages like Python, SQL, and R and for data manipulation, analysis and model building
Machine learning algorithms and techniques
3+ years of experience building models including deep learning, neural network algorithm development
Prediction, Forecasting, A/B testing, complex modeling and data analyses
Responsibilities
Developing and implementing statistical models and machine learning algorithms to analyze relevant structured and unstructured datasets and variables
Developing ML models and planning end-to-end ML model experiment design
Understanding and translating business needs and objectives into the appropriate modeling technique
Applying hypothesis testing, regression, A/B testing and time-series forecasting to product creation decisions and timelines
Building and maintaining predictive/prescriptive models for scale working closely with ML Engineers to turn successful prototypes in to new AI products
Working closely with product and engineering teams to build, support, and scale these data-driven insights into product merchandising plans & assortments and product design recommendations
Evaluating existing ML and statistical products to ensure continued high-quality results and outputs
Other
Ability to communicate complex data in a simple, actionable way to non-technical audiences and leadership teams
Ability to work independently and with a diverse team
PhD in Data Science, Applied Statistics or related field. Will accept any suitable combination of education, experience and training
3+ years of experience building models including deep learning, neural network algorithm development
Ability to proactively engage with business stakeholders, listen deeply to business challenges, and translate them into well-defined data science problems
