People, Person, Apparel, Clothing

SR DATA SCIENTIST

SR DATA SCIENTIST

Portland | Oregon | United States

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.

Marketing, Marketing & Communications

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.

The Nike, Inc. Communications team develops, establishes and strengthens authentic connections with diverse audiences through the lens of innovation and sport. The team creates premium and innovative brand stories, builds and enhances corporate reputation and brand equity, and engages audiences such as consumers, media, athletes, investors, non-governmental organizations and Nike's own employees. The team focuses on information, inspiration and connection to accelerate the growth of Nike, Inc. Communications employees ignite conversations, envision the possibilities, and influence and deliver new levels of creative and strategic thinking to advance the brand around the world.
Description

Nike does more than outfit the world's best athletes. We are a place to explore potential, obliterate boundaries, and push out the edges of what can be.

Based in Beaverton, Oregon, the Personalization Scientist will join an established team, which sits within Nike's Global Decision Science Center of Excellence is a fast growing team responsible for building and deepening a holistic view of Nike's consumers through data and analytics, and applying those insights to personalize and optimize incredible digital services and experiences for our consumers.

We are looking for scientists with tech industry experience to help build our core data products and machine learning and statistical modeling processes. We want someone who loves modeling and writing code, someone who likes to dive in, solve problems, and create world class experiences for Nike consumers. This is a young and growing team, so the ideal candidate is ready for a leadership role in a collaborative environment, helping to drive team excellence and defining and socializing best practices for the team. We are deeply integrated with our partner data and services engineering teams, and collaborate extensively with all of Nike's digital product teams to help drive design and then deliver personalized experiences. You should be ready for partnership with teams across the company and excited about green spaces in which to make your mark.

A candidate should be experienced in state of the art statistical modeling or machine learning algorithms, but also be able to think in terms of the compute processes, distributed data, and coupling between systems.

We're looking for scientists who thrive in a dynamic setting. Communication and leadership skills are key. You'll get to work with scientists with a breadth of experiences across industry and academia, including in machine learning, statistics, neuroscience, and physics. You'll be expected to go deep and learn with them, as a peer and as a team.

Key responsibilities will include some of:

• Develop models that drive personalization of digital experiences for Nike consumers - e.g. suggesting products with an aesthetic match to products a consumer has shown interest in through computer vision, consumer behavior patterns, or some new approach you devise.
• Develop models that help us understand and describe our customers - e.g. learning how to extract deep interests and tendencies from event streams.
• Develop production code for both batch and real time models in collaboration with our data and service engineering teams.
• 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.

• B.S. in CS, statistics, applied math, physics or other quantitative discipline
• Advanced degree (Masters or PhD) preferred


Qualifications
• A minimum of 2 years' of experience in a role developing predictive or explanatory models and/or experimentation processes
• Experience working with data and analytics
• Experience with moderate to large-scale data sets (>100GB) preferred
• Experience with neural nets and deep architectures preferred

Required Skills
• Core mathematical ability to understand, utilize and innovate on state-of-the art machine learning algorithms and/or statistical modeling
• Expertise in at least one production-quality programming languages (e.g. java, python, scala, C++)
• Exceptional communication skills
• Expertise with Hadoop ecosystem (especially spark) is a plus
• Expertise with ETL processes is a plus

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.

Job ID 00446680

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