Únete al equipo de NIKE, Inc.

NIKE, Inc. no solo viste a las mayores estrellas del deporte del mundo. También te permite explorar tu potencial, romper las barreras e ir más allá de lo que creías posible. Buscamos personas capaces de crecer, pensar, soñar y crear. La cultura de la empresa anima a aceptar la diversidad y recompensar la imaginación. Necesitamos personas sin miedo al éxito, líderes y con una mentalidad visionaria. En NIKE, Inc. todo el mundo aporta sus habilidades y pasiones, en un entorno exigente en continuo cambio.

Open to remote work except in South Dakota, Vermont and West Virginia.

The annual base salary for this position ranges from $107,700.00 in our lowest geographic market to $212,600.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.

Information about benefits can be found here.

WHO WE ARE LOOKING FOR 

We’re looking for a Data Scientist III to join our Reporting + Intelligence team in the Consumer Product & Innovation organization. You will work with diverse cross-functional team members leveraging data-driven insights and AI to inform and optimize all stages of Nike's merchandising and apparel & footwear product creation lifecycle.   

WHAT YOU WILL WORK ON 

You will partner with cross-functional teams to develop data-driven insights, predictive models, and optimization solutions for Nike's apparel and footwear product merchandising, design and development functionsLeveraging your deep expertise in statistical analysis, machine learning, and applied data science you will help solve complex problems across the apparel and footwear product lifecycleYou will be responsible for developing scalable models, conducting exploratory data analysis, and generating actionable insights that drive data-driven decisions for our merchants and creators. 

 

You will be responsible for: 

  • Developing and implementing statistical models and machine learning algorithms to analyze relevant structured and unstructured datasets and variables (Merchandising Product Lines and Assortments, Apparel & Footwear Design and Development, Sales, Consumer Behavior, Market Trends. etc.)  

  • Developing ML models and planning end-to-end ML model experiment design  

  • 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 

  • Performing data and error analysis to improve model performance 

  • Creating clear and compelling visualizations to communicate findings and recommendations 

  • Identifying and making recommendations on analytical tools, research tools, methods 

 

WHO YOU WILL WORK WITH 

You will spend much of your time with peer data scientists, machine learning engineers, and merchandising, apparel and footwear creation Product Managers in CP&I delivery teams.   

 

WHAT YOU BRING 

  • Strong statistical and mathematic foundationSolid understanding and practical application of statistical concepts, probability and hypothesis testing 

  • Extensive experience with cloud tools for data science, machine learning and modeling, and visualization e.g., Jupyter Notebooks, RStudio, pandas, PySpark, SageMaker, Databricks, MLFlow, Tableau, PowerBI 

  • Expertise in languages like Python, R, and SQL for data manipulation, analysis and model building 

  • Machine learning algorithms and techniques 

  • 3+ years of experience building models  

  • 3+ years of deep learning, neural network algorithm development 

  • Prediction, Forecasting, A/B testing, complex modeling and data analyses 

  • GenAI and building LLM prototypes 

  • Developing and running simulation and optimization tools to support decision making 

  • Ability to visualize data in the most effective way possible  

  • 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 or related field. Will accept any suitable combination of education, experience and training

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

Qué ocurrirá

PROGRAMA DE CONTRATACIÓN

01. Presenta una solicitud

Nuestros equipos son diversos y están formados por personas que aportan capacidades, conocimientos, ideas y experiencias diferentes. Queremos que encuentres el trabajo perfecto para ti, así que lee las descripciones de los puestos, los departamentos y los equipos.

02. Conoce al/a la responsable de la selección de personal o haz una evaluación

Si te seleccionan para ocupar un puesto corporativo, la persona responsable de la contratación te contactará para comenzar las entrevistas y será tu punto de contacto principal durante todo el proceso. Para los puestos de Retail, tendrás que completar una evaluación interactiva de entre 10 y 20 minutos que incluye una conversación y cuestionarios. Independientemente de tu puesto, queremos conocer todas tus facetas, así que no tengas reparo en enseñar cómo ofreces un servicio premium y qué es lo que te diferencia de los demás.

03. Haz una entrevista

Enfréntate a esta fase con confianza. Para ello, investiga, entiende lo que buscamos y prepárate para responder a las preguntas que te hagan para conocerte mejor a ti y a tu experiencia.

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