Data Scientist/Architect - IntermediateHybrid

Title: Data Scientist/Architect - Intermediate

Location: Beaverton, OR

Duration: 2 Year Contract

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.

WHAT YOU WILL WORK ON

• Design, develop and program methods, processes, and systems to consolidate and analyze structured/unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.
• Build "products" for Analysis. Interact with product and service teams to identify questions and issues for data analysis and experiments.
• Develop and code software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
• Identify meaningful insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to product, service, and business managers.
• Lead to the accomplishment of key goals across consumer and commercial analytics functions.
• Work with key stakeholders to understand requirements, develop sustainable data solutions, and provide insights and recommendations.

WHAT YOU BRING

• Bachelors Degree and minimum of 2-4 years directly relevant work experience
• Skill in SQL queries and data visualizations to fulfill ad-hoc analysis requests and ongoing reporting needs leveraging standard query syntax
• Ability to organize and transform information into comprehensible structures
• Knowledge of using data to predict trends and perform statistical analysis
• Experience with data mining to extract information from data sets and identify correlations and patterns
• Understanding of monitoring data quality and removing corrupt data
• Capability to evaluate and utilize new technologies, tools, and frameworks centered around high-volume data processing
• Skill in improving existing processes through automation and efficient workflows
• Competence in building and delivering scalable data and analytics solutions
• Capacity to work independently and take initiative to identify, explore and solve problems