Senior Research Data Scientist at Nike
NYC, New York, United States
🇺🇸 (Posted Jul 8 2018)
About the company
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.
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 research data scientist with tech industry experience to work in our research group and help improve our core predictive models. You should have a proven track record of completing research, preferably in predictive modeling. Specifically, we want someone who has an excellent knowledge of statistics and machine learning methodology (preferably at the Ph. D. level). Additionally, you must love writing code and have exceptional R or Python programming skills.
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 other data scientists. 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 machine learning, statistics, marketing, and finance. You’ll be expected to go deep and learn with them, as a peer.
Job Duties and Responsibilities:
• Research and develop accurate models that predict customer behavior and customer lifetime value using Bayesian, frequentist, and machine learning methodologies.
• Collaborate with other data scientists to solve problems necessary to address key business questions.
• Build models that elucidate the causal effects of marketing on customer lifetime value and customer behavior.
• Productionize predictive models for use in a containerized environment.
Skills & requirements
• 1+ years post grad experience developing predictive or explanatory models and/or experimentation processes
• Strong demonstrated ability to do research and develop mathematical models
• Stellar programming ability in Python or R
• Deep understanding of statistics, Bayesian methods, and machine learning methodology including tree methods, and regression.
• Experience with empirical Bayes a strong plus
• Experience with causal inference is a plus
• Expertise with at least one production-quality programming language is desirable (e.g. C/C++)
• Exceptional communication abilities
• Experience working with real-world data and analytics
• 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)
• Ph. D. in applied mathematics, statistics, or machine learning or equivalent research experience in industry.
Instructions how to apply
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