(usa) Staff, Data Scientist

Walmart Walmart · Retail · SUNNYVALE TECH CORNERS BLDG 6 CA SUNNYVALE

Staff Data Scientist at Walmart focused on developing and implementing advanced analytical techniques and machine learning to transform complex data into actionable business insights for Search, Personalization, and Advertising platforms. The role involves data strategy, model development, validation, and deployment in production environments, with a focus on improving customer engagement and driving business value.

What you'd actually do

  1. Identify and source relevant data from multiple business domains, ensuring data quality and suitability for analysis.
  2. Develop and implement data strategies aligned with business objectives to unlock value from data assets.
  3. Build, assess, and validate predictive models using advanced statistical and machine learning techniques.
  4. Create clear, insightful data visualizations to communicate findings effectively to stakeholders.
  5. Translate complex business problems into data-driven solutions and actionable insights.

Skills

Required

  • Python programming
  • data visualization tools (Matplotlib, Plotly, Tableau, or PowerBI)
  • data strategy
  • data quality assessment
  • data governance
  • identifying suitable data sources
  • SQL
  • NoSQL
  • natural language processing
  • deep learning
  • MLOps

Nice to have

  • Machine learning
  • optimization models
  • PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics
  • Python, Spark, Scala, or R
  • scikit learn
  • tensorflow
  • torch
  • Web Content Accessibility Guidelines (WCAG) 2.2 AA

What the JD emphasized

  • advanced analytical techniques
  • machine learning
  • data strategy
  • model development
  • predictive models
  • machine learning algorithms
  • natural language processing
  • deep learning
  • MLOps

Other signals

  • Develop and implement data strategies aligned with business objectives to unlock value from data assets.
  • Build, assess, and validate predictive models using advanced statistical and machine learning techniques.
  • Collaborate with cross-functional teams to deploy and scale models in production environments.