Director, Member Data Science
Posted on Nov 17, 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
- Tutition Reimbursment
- Paid Time Off/Summer Fridays
- Family Support
- Relocation Reimbursement
- Work/Life Balance
- Company Wide Volunteering
Nike, Inc.'s storytellers, Marketing and Communication sets the brand tone. A creative force of specialists tell Nike's stories of innovation and sport through advertising, brand strategy, digital engagement and product presentation. Using channels ranging from retail stores to social media, Marketing & Communication teams connect the science and art of Nike innovations to the hearts and minds of athletes around the world.
Nike's Member Data Science 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 and growth of incredible digital services, content and experiences for our consumers.
We are looking for a Director of Data Science with tech industry experience to help build our core data products and modeling/experimentation processes. We want someone who loves modeling and writing code. This is a young and growing team, so the ideal candidate is ready for a leadership role, defining and socializing best practices for the team.
We are looking for someone who is comfortable with state of the art modeling or machine learning algorithms, but can also think in terms of the compute process and coupling between systems. The role will focus on developing production models to understand and predict consumer behavior, including lifetime value, segmentation, and affinity modeling.
We're looking for someone who thrives in a dynamic setting. Communication and leadership skills are key. You'll get to work with scientists and engineers with a breadth of experiences across industry and academia, including in machine learning, statistics, marketing, econometrics, and finance. You'll be expected to go deep and learn with them, as a peer.
Job Duties and Responsibilities:
- Develop models that help us understand and describe our customers, e.g. learning how to extract deep interests and tendencies from event streams.
- Manage an experimentation portfolio that validates and feeds back into our core customer understandings.
- Build processes to support fast, iterative experimentation, both for model creation and for customer-facing products.
- Define best practices for scientific code development and deployment.
- 7+ years experience developing predictive or explanatory models and/or experimentation processes
- Core mathematical ability to understand, utilize and innovate on state-of-the-art machine learning algorithms and/or statistical modeling
- Expertise with at least one production-quality programming language (e.g. Python, C++)
- Exceptional communication abilities
- Experience working with real-world data and analytics
- Experience with moderate to large-scale data sets (>100GB) preferred
- Experience with customer lifetime value and segmentation algorithms a plus
- Experience working in a production environment including best practice tools (e.g. cloud architecture, version control)
- Experience as a lead preferred
- Experience with R a plus
- BS in CS, statistics, applied math, physics, or other quantitative discipline
- Advanced degree (Masters or PhD) preferred
7+ years experience developing predictive or explanatory models and/or experimentation processes
Core mathematical ability to understand, utilize and innovate on state-of-the-art machine learning algorithms and/or statistical modeling
Expertise with at least one production-quality programming language (e.g. Python, C++)
Exceptional communication abilities
Experience working with real-world data and analytics
Experience with moderate to large-scale data sets (>100GB) preferred
Experience with customer lifetime value and segmentation algorithms a plus
Experience working in a production environment including best practice tools (e.g. cloud architecture, version control)
Experience as a lead preferred
Experience with R a plus
BS in CS, statistics, applied math, physics, or other quantitative discipline
Advanced degree (Masters or PhD) preferred