Conviértete en parte del equipo de NIKE, Inc.
NIKE, Inc. hace más que vestir a los mejores atletas del mundo. Es un lugar para explorar el potencial, borrar límites y ampliar los límites de lo que puede ser. La empresa busca personas que puedan crecer, pensar, soñar y crear. Su cultura prospera al abrazar la diversidad y recompensar la imaginación. La marca busca triunfadores, líderes y visionarios. En NIKE, Inc. se trata de que cada persona aporte habilidades y pasión a un juego desafiante y en constante evolución.
Lead Data Scientist- Nike Inc.- Beaverton, OR. Work closely with Data Science and Engineering teammates to build, support, and enable end-to-end personalized shopping experience use cases. Build credibility for algorithmic approaches through demonstrating functional expertise and experience. Innovating to drive more temporally precise engagement, and broader adoption across the organization. Establish and support large-scale measurement and optimization of consumer experiences for different geographies in a production/testing environment. Enhance and consult on best Search and Recommender System practices to connect the impact of marketplace drivers and business short-term and long-term outcomes. Partner with peers in both Data Science and Engineering, developing scalable data, improving current models, systems, and modeling processes. Utilize common tools and instruments to help establish operational excellence for Nike. Drive the application and implementation of innovative best-in-class methods and tools to derive useful insights for a wide variety of business goals in support of merchandising efforts. Stay up to date on industry trends, tools, and platform capabilities relevant to the team’s disciplines. Telecommuting is available from anywhere in the U.S., except from AK, AL, AR, DE, HI, IA, ID, IN, KS, KY, LA, MT, ND, NE, NH, NM, NV, OH, OK, RI, SD, VT, WV, and WY.
Must have a Master's degree in Computer Science, Data Science and two (2) years of experience in the job offered or data-related occupation. Experience must include the following:
- Building and maintaining predictive and/or prescriptive models in production at enterprise scale
- Synthesizing and packaging complex analyses and delivering results to non-technical audiences including executive leadership teams
- Developing and running simulation and optimization tools to support decision making
- Python and SQL
- Machine Learning (Regression, Classification, Clustering) and Deep Learning(MLP, LSTM, CNN);
- Time Series Modeling
- Design of Experiments
- Cloud Services (Amazon Web Services)
- Spark and Hadoop
- Data Visualization (Tableau)
- Scheduling Tools (Airflow)
- Agile Development Process
- Quality Assurance Testing and Automation
Apply at www.Nike.com/Careers (Job# R-61369)
#LI-DNI
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.
NUESTRO PLAN DE CONTRATACIÓN
01 Postúlate
Nuestros equipos están formados por diversos conjuntos de habilidades, bases de conocimientos, contribuciones, ideas y antecedentes. Queremos que encuentres la opción perfecta: revisa las descripciones de los puestos, los departamentos y los equipos para descubrir la función ideal para ti.
02 Habla con un reclutador o haz una evaluación
Si te seleccionan para un puesto corporativo, un reclutador se pondrá en contacto contigo para iniciar tu proceso de entrevistas y será tu contacto principal durante todo el proceso. En el caso de los puestos de Retail, tendrás que realizar una evaluación interactiva que incluye una conversación y cuestionarios. Te tomará entre 10 y 20 minutos completarla. Independientemente del puesto, queremos conocerte a ti, a tu yo en su totalidad, así que comparte quién eres, qué te hace singular y qué deseas hacer.
03 Entrevista
Entra en esta fase con confianza: investiga, entiende lo que buscamos y prepárate para las preguntas que nos harán saber más sobre ti y tus antecedentes.
