Senior Data Scientist - Nike - Portland

Job description
Data Scientist, Integrated Analytics, Global Consumer Knowledge
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. Nike’s Global Consumer Knowledge Center of Excellence is responsible for building and deepening a holistic view of Nike’s consumers through data and analytics. We are looking for a senior statistician to work across Nike’s consumer facing businesses to define and implement measurement strategies, instrument and analyze consumer behavior, and inform Nike’s global strategy. The ideal candidate will have a deep passion for applying advanced analytic approaches, an eagerness to dig into the data, and a vision for turning disparate data streams into a cohesive view of our global consumers.

Key responsibilities:
Leading the creation of a comprehensive view of relevant consumer behaviors, incorporating a wide variety of signals, data types, and sources
Assessing the potential usefulness, validity, and rigor of new data sources or analytic approaches and the capabilities of potential partners

Proposing measurement strategies to translate business goals into KPIs across Nike’s consumer-facing businesses
Executing on projects utilizing advanced analytic approaches in order to inform Nike’s strategy
Partnering with Nike’s technical and legal teams to design and improve consumer data infrastructure

Desired Skills and Experience
Education:
Degree in statistics, econometrics, applied math, or a quantitative behavioral sciences field
Advanced degree (MA or PhD) strongly preferred but not required


Experience
At least 8 years in an applied analytics or quantitative research role
Experience in applying advanced analytics to inform product or marketing strategy and/or to develop and improve digital services is a plus

Required Skills
A deep understanding of applied statistics including sampling approaches, causal modeling, time series analysis, and data mining techniques
Experience in the valuation and definition of new consumer measures, and the translation of business goals into quantitative metrics
Experience in working with large structured and unstructured data sets; experience working with Hadoop environment a plus
Fluency with SAS or R; additional experience with Python or other programming languages preferred
Ability to independently execute large research projects with multiple business stakeholders on firm deadlines
An understanding of key topics and literature in marketing science, data science, and applied analytics

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