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Dynamic Entry‑Level Remote Data Analyst – Nike ...

Worldwide Salaried Open

About Nike: A Global Leader Powered by Passion and Innovation At Nike, we are more than a world‑renowned sportswear brand – we are a cultural catalyst that inspires athletes of every ability to push beyond limits. For over 50 years, Nike has pioneered cutting‑edge product design, groundbreaking technology, and bold storytelling that reshapes how people experience sport, fitness, and everyday life. Our commitment to “bringing inspiration and innovation to every athlete in the world” extends to every corner of the organization, including the data‑driven insights that fuel strategic decisions across product development, marketing, supply chain, and digital experiences. Joining Nike means becoming part of a purpose‑centric community that values diversity, creativity, and relentless curiosity. As a remote employee, you will experience the same high‑performance culture that defines our physical offices, while enjoying the flexibility to work from wherever you feel most productive. Position Overview: Entry‑Level Remote Data Analyst The Entry‑Level Remote Data Analyst role is a gateway to a rewarding analytics career within a globally recognized brand. You will collaborate with seasoned data professionals, product managers, and marketing strategists to translate raw data into actionable intelligence that shapes the future of sportswear, digital experiences, and consumer engagement. This is a fully remote, full‑time position that offers immediate start dates for motivated candidates.

Key Responsibilities

  • Data Collection & Preparation: Gather data from internal systems (e.g., sales dashboards, e‑commerce platforms, supply‑chain tools) and external sources (market research, social media trends). Clean, normalize, and validate datasets to ensure accuracy before analysis.
  • Exploratory Data Analysis (EDA): Conduct thorough EDA using statistical techniques and visual storytelling to uncover patterns, correlations, and anomalies that inform business questions.
  • Analytical Modeling & Insight Generation: Build predictive and descriptive models in Python or R to support forecasting, segmentation, and performance measurement. Translate model outputs into clear, data‑driven recommendations.
  • Dashboard & Report Development: Design interactive visualizations in Tableau, Power BI, or Looker that enable stakeholders to monitor key performance indicators (KPIs) in real time. Ensure reports are user‑friendly and aligned with brand standards.
  • Cross‑Functional Collaboration: Partner with product development teams, digital marketers, finance, and supply‑chain specialists to understand data needs, refine analytical questions, and co‑create solutions.
  • Data Governance & Quality Assurance: Implement best practices for data lineage, documentation, and version control. Perform regular audits to maintain high data integrity across all analytical assets.
  • Continuous Learning & Industry Awareness: Stay current with emerging analytics tools, sports industry trends, and consumer behavior insights. Bring fresh ideas to the team and contribute to the evolution of Nike’s analytics roadmap.

Essential Qualifications

  • Educational Background: Bachelor’s degree in Business Analytics, Statistics, Computer Science, Economics, or a related quantitative discipline (or equivalent practical experience).
  • Technical Proficiency: Demonstrated ability to manipulate data using Excel (advanced functions, pivot tables) and at least one programming language such as Python or R for data cleaning, analysis, and modeling.
  • Statistical Foundations: Solid understanding of descriptive statistics, hypothesis testing, regression analysis, and basic forecasting methods.
  • Data Visualization Skills: Practical experience creating dynamic dashboards and visual reports with Tableau, Power BI, or similar tools, focusing on clarity, storytelling, and actionable insights.
  • Problem‑Solving Mindset: Proven track record of breaking down complex business problems, developing analytical approaches, and presenting concise recommendations.
  • Communication Excellence: Strong written and verbal communication abilities, capable of translating technical findings into language that resonates with non‑technical audiences.
  • Team Orientation: Demonstrated collaboration in cross‑functional settings, with a proactive attitude toward sharing knowledge and supporting teammates.
  • Remote Work Readiness: Self‑discipline, reliable internet connectivity, and a comfortable home office setup that meets professional standards. Preferred Qualifications (Nice to Have)
  • Internship or project experience in a consumer‑focused industry, especially apparel, footwear, or e‑commerce.
  • Familiarity with cloud‑based data platforms such as Snowflake, bolthires BigQuery, or AWS Redshift.
  • Exposure to machine‑learning libraries (scikit‑learn, TensorFlow) for building simple predictive models.
  • Knowledge of SQL for querying relational databases.
  • Certification in data analytics or visualization (e.g., Tabl

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