Data Science Engineer, Membership Data Science
Posted on Nov 16, 2018 by Nike
Overview NIKE Digital is taking technology into the future and bringing the world with it. At NIKE Digital, we embrace open source, contributing to the community by building - and sharing - digital solutions that work on a global scale. We invest in cutting-edge technologies and work with a network of open source libraries and tools, like React.js, Node.js and GraphQL. These investments and tools help us advance web and native UI development, evolve our data science and eCommerce capabilities, refine our DevOps and retool our services infrastructure.
We're passionate about NIKE and all the swoosh represents: limitless drive, innovation, creativity and possibilities for collaboration. We focus relentlessly on talent and are always looking for ways to encourage growth. We are inspired by the NIKE legends who built an empire rethinking product and service, and we seek to bring that level of innovation to our technologies. Our vision is to build and deliver extraordinary NIKE platforms, services and products directly to athletes* around the world.
*If you have a body, you're an athlete.
- Full Time
- Level: Corporate
- Travel: Minimal
Success Profile At Nike Digital, we're revolutionizing fitness and sport. We're creating personalized digital experiences that inspire athletes to move faster, push harder and acheive their personal best. As a team, we're motivated by Nike's proud legacy of always being first. Join our world-class technologists in finding innovative ways to engage consumers and strengthen their connection to our products, services and brand. The work you do today will help modernize the workplace and prove essential to Nike's future success and growth.
- Digitally Savvy
- Technologically Savvy
- socially conscious
- team player
Nike gives me the freedom to create, to innovate, to fail. Our team is encouraged to experiment and take risks, a process out of which our digital future grows. Chris Peddecord Front End Engineer, Nike Digital
Nike is one of the biggest and most prestigious brands. Making nike.com live up to that prestige and work at a global scale, is the kind of challenge that brings me back to work, day-after-day. Ryan Miller Technical Architect
- Tuition Reimbursment
- Paid Time Off/Summer Fridays
- Family Support
- Relocation Reimbursement
- Work/Life Balance
- Company Wide Volunteering
Nike's Membership Data Science Engineering is a growing organization responsible for building and deepening a holistic view of Nike's consumers through data and analytics and applying those insights to inform the development of incredible digital services, content and experiences for our consumers.
We are looking for a data engineer that can bridge the gap between our engineering and data science teams. This individual will work with the data science team at Membership Data Science to help build the data pipelines that power the data science platform. Expert knowledge of data engineering and writing data pipelines is essential. We're also looking for someone with a basic understanding of data. The right candidate will have experience utilizing the latest data engineering tools and techniques.
We're looking for someone who thrives in a dynamic setting and can work as part of a team. You'll be working collaboratively with data scientists and engineers. Communication skills are key for this position and you'll be expected to clearly explain your methodology and findings to other data scientists, engineers, and team leadership. You'll get to work with scientists with a breadth of experiences across industry and academia, including in engineering, statistics, marketing, and finance. You'll be expected to go deep and learn with them, as a peer.
- Background in a related field such as computer science, computer information systems or mathematics.
- 3+ years' experience data science or engineering.
- Strong understanding of databases, including BigQuery
- Experience using one or more following languages Python, C++, R, Julia, Go.
- Experience with distributed programming tools like Airflow, MapReduce, Spark, etc.
- Experience working in with containerization.
- Experience with Kubernetes is plus.
- Experience working with high volume data management.
- Strong communication skills
- A basic understanding of data science