Become a Part of the NIKE, Inc.

Team NIKE, Inc. does more than outfit the world's best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The brand seeks achievers, leaders and visionaries. At Nike, it’s about each person bringing skills and passion to a challenging and constantly evolving game.

WHO ARE WE LOOKING FOR 

 

As a Software Engineer within the AIML team, you will be developing sophisticated analytics systems that directly impact our business.  You will work on a cross-disciplinary team (Machine Learning / Software Engineering / DevOps) to enable data-driven decision-making across multiple organizations. Working at the intersection of machine learning and software engineering, you’ll create high-quality solutions that power Nike. You will work with others who are energized by the challenge of building things from the ground up, thinking out of the box, and applying the latest technologies in statistical, unsupervised, supervised, and machine-learning models at a global scale. Our teams enjoy a collaborative and academic environment that promotes developing new skills, mentorship, and a drive to deliver knowledge and software back to analytics and engineering communities, within and Nike and without. This culture is cultivated by intellectual curiosity, fun, willingness, and diversity. 

WHO WILL YOU WORK WITH 

 

AIML is one of the key groups within Data and Artificial Intelligence. We’re chartered to scale machine learning and AI at Nike. For areas of the business early in their analytics journey, we embed cross-disciplinary teams of data scientists and engineers to unlock new capabilities and answer unsolved (or unasked!) questions. 

In mature areas with preexisting data science teams, we help scale machine learning by attaching engineering squads to grow their capacity to deliver for the business. In addition, we collaborate closely with platform and architecture partners to develop capabilities that simplify machine learning at scale within Nike (e.g. model deployment, A/B testing, model monitoring). 

WHAT YOU BRING TO NIKE

  • Understanding of Python programming and ability to write simple, clear code 

  • Familiarity with version control systems like Git 

  • Familiarity with SQL and Spark basics 

  • General awareness of data science concepts and common machine learning algorithms 

  • Understanding of cloud computing concepts (e.g., AWS, Google Cloud) 

  • Educational background or coursework in mathematics, statistics, or computer science 

  • Understanding of basic software design principles 

  • Good communication skills and ability to work in a team environment 

  • Willingness to learn and grow in areas of data science and software development 

NIKE, Inc. is a growth company that looks for team members to grow with it. Nike offers a generous total rewards package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Nike employee shares one galvanizing mission: To bring inspiration and innovation to every athlete* in the world. 

NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability. 

#LI-EMEA 

 

기대할 수 있는 사항

채용 계획

01 지원

나이키 팀은 다양한 기술과 지식, 의견, 아이디어, 배경을 가진 사람들로 구성되어 있습니다. 직무 소개서와 부서, 팀을 살펴보며 내게 맞는 역할을 찾아보세요. 적합한 직무를 찾을 수 있기를 바랍니다.

02 채용 담당자와의 만남 또는 평가 진행

본사 직무에 선발되면 면접 과정을 시작하고자 채용 담당자가 연락을 드립니다. 해당 과정을 진행하는 동안 이 담당자와 주로 연락하게 됩니다. 리테일 직무의 경우 채팅과 퀴즈 등 양방향 평가가 진행되며, 완료하는 데는 약 10~20분이 소요됩니다. 어떤 직무에 지원하시든, 나이키는 여러분에 관한 모든 정보를 듣고 싶습니다. 그러니 여러분이 어떻게 세계 최고 수준의 서비스를 제공할 것인지, 여러분만의 특별함은 무엇인지 주저하지 말고 보여주시길 바랍니다.

03 면접

이 단계를 자신 있게 시작하기 위해 필요한 정보를 조사하고 나이키가 추구하는 요소를 파악해 보세요. 또 여러분과 여러분의 배경에 관해 자세히 알기 위해 고안된 질문에 답할 준비를 갖추세요.

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