Expert Data Analyst

NIKE, Inc.
NIKE, Inc.

Job Overview

WHO ARE WE LOOKING FOR:Our Enterprise Data and Analytics team is looking for a skilled Expert Data Analyst to guide development of our next generation consumer data systems and deliver critical capabilities to unlock marketing, personalization and advance analytics. This role demands passion for research, analytics, and forensics to find and surface hidden patterns in complex data ecosystems. In this role, you’d guide the development of Consumer Data Platform to serve attributed marketing needs on owned and paid platforms.WHO WILL YOU WORK WITH:You will partner closely with the several business units, engineering, technology, data science and product teams on daily basis to deliver solutions that solve critical business problems as we accelerate our Consumer Direct strategies!WHAT WILL YOU WORK ON:* Conceptualize, develop and execute statistical and ML models to power business decision making, requirement assessment and critical initiatives. You would also help establish strong data foundation for critical data and analytics solutions.* You would build confidence in Consumer data assets and capabilities, and promote adoption of data driven decision analytics to guide business leaders and engineering* Conduct ad hoc quantitative analyses, modeling, or programming using Databricks, SQL, R, or Python.* Develop marketing attribution and consumer engagement models using statistical methodologies and machine learning techniques for marketing campaigns.* Partner with business teams to identify their needs and develop and implement modeling solutions* Assist business and engineering teams with assessing quality of data and validity of business hypothesis through back testing against realized outcomes, bench marking against alternative models and other relevant tests.* Research and develop quantitative tools and techniques to measure and analyze consumer engagement, potential opportunities and business risks.* Assess conceptual foundations of a business requirements, data model, ML model specification, underlying assumptions, limitations, variable selection, underlying data, developmental evidence, documentation.* Assist product managers in production of regular and ad-hoc reports for senior management and business partners.* Guide and support data engineering teams with data specification, important metrics, and data validation queries/programs.

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