Nike-posted 2 months ago
$89,800 - $177,200/Yr
Remote • New York, NY
5,001-10,000 employees
Leather and Allied Product Manufacturing

The Digital Loss Prevention (DLP) team are experts at identifying fraud, abuse and systematic loopholes that result in financial losses in North America. They work as a team to deliver solutions that protect profit and reduce friction for our members to maximize investment in the business and deliver the best possible product to consumers. This role will report to the DLP Analytics manager and work closely with the DLP Quality Assurance and Fraud Insights team. We are looking for a Business Intelligence Data Analyst to join the NA DLP team. You will be expected to be a self-starter and an agile problem solver with comfort and curiosity in leveraging experience to solve complex data problems and learning new techniques as required. The ideal candidate takes ownership in all 3 phases of great data work: technical excellence in writing efficient code/pipelines, implement strong data visualization principles to aim at business questions, turn information to insight and communicate to technical and non-technical stakeholders.

  • Provide support for Nike Direct Digital Loss Prevention in North America.
  • Use data to reduce risk from abusive customers and reduce friction and inefficiency throughout Nike Direct to all consumers.
  • Learn and deliver insights and solutions to improve operational efficiency.
  • Act as a Subject Matter Expert (SME) within the department and provide mentorship and assistance to internal and cross-functional teammates.
  • Take end-to-end ownership of accurate and agile data products/dashboards.
  • Work in ambiguity to solve open-ended business problems with all available Nike data sets.
  • Bachelor's degree in data science, statistics, math, computer science, business analytics or related field.
  • 2+ years of experience synthesizing insights from data.
  • Highly Advanced knowledge of SQL and relational databases; experience with concepts such as Window Functions, Complex Joins, PIVOT/UNPIVOT, query optimization.
  • Strong understanding of data visualization principles and experience with at least one dashboarding tool (Tableau, Power BI, Looker, etc.).
  • Demonstrated ability to build self-serve tools for technical and non-technical stakeholders that answer common questions and/or increase data literacy across the organization.
  • Ability to design metrics that help evaluate the health of the business and the success of our team, including any ETL development needed.
  • Demonstrated ability to take ambiguous problems and solve them in a structured, hypothesis-driven and data-supported way.
  • Familiarity with Python/R for scripting, predictive and descriptive modelling, and data visualization.
  • Experience with Tableau; including optimizing published work in Tableau server.
  • Familiarity with data warehousing tools Databricks and/or Snowflake.
  • Experience in Fraud, DLP or digital commerce analytics.
  • Background with analytics tools (Spark, Git, Jupyter) and cloud computing platforms (AWS preferred).
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