Data Analytics Manager

Key Skills

Java Programming, Python Programming, SQL, Data Visualization, Tableau, Snowflake, Statistical modeling, Data pipelines, ETL frameworks, Data Architecture, Data Analysis

Job Description

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, Inc. it’s about each person bringing skills and passion to a challenging and constantly evolving game.

Nike USA Inc., Boston, MA. Identify and apply appropriate methods to acquire, explore, cleanse, and fuse data from different sources. Take initiative and deploy quantitative research to identify, explore, fix and solve problems related to data coverage and quality. Coordinate with multi-functional partners and manage analytics products with multiple business partners on established deadlines. Participate in the development of new algorithms and enhancement of existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast consumer demand and determine optimal level of investment in various stages of the supply chain. Communicate systems/analytics changes to the business, translating complex functionality into business relevant language. Collaborate with key partners to understand requirements, drive knowledge into action and support data driven decision making.

Applicant must have a Master’s degree in Computer Science, Engineering, Information Systems, Business Administration, Economics, or Mathematics and 2 years of experience in the job offered or a related occupation. Experience must include:

• SQL;
• Data visualization;
• Data architecture;
• Data pipelines;
• ETL;
• Project management, including defining project priorities and scheduling project deadlines;
• Tableau;
• Snowflake;
• Statistical Analysis;
• Data Issue Triage;
• Technical code reviews; and
• Scrum and Agile principles.