(usa) Principal, Data Scientist

Walmart Walmart · Retail · Sunnyvale, CA

Principal Data Scientist to lead development and deployment of advanced analytical models and machine learning solutions for complex business challenges. Focus on data governance, cloud-native platforms, and model-driven design to support AI/ML integration.

What you'd actually do

  1. Develop, test, and deploy advanced data science solutions using appropriate programming languages and tools.
  2. Analyze complex business problems to identify root causes and recommend effective, data-driven strategies.
  3. Identify and validate suitable data sources, ensuring data quality and relevance for modeling and analysis.
  4. Design, build, and validate predictive models leveraging machine learning and statistical techniques.
  5. Collaborate with stakeholders to translate business requirements into actionable data science initiatives.

Skills

Required

  • Python
  • Statistical analysis
  • Machine learning
  • Data visualization
  • Data governance
  • Model deployment
  • Cloud platforms (AWS SageMaker)

Nice to have

  • Spark
  • Scala
  • R
  • scikit-learn
  • tensorflow
  • torch
  • Data science
  • Machine learning
  • Optimization models
  • PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics
  • Publications or active peer reviewer in related journals or conference

What the JD emphasized

  • Extensive experience in developing and deploying machine learning models using Python and related programming languages.
  • Proficiency in statistical analysis, advanced modeling techniques, and exploratory data analysis to solve complex business problems.
  • Expertise in data source identification, data quality assessment, and applying data governance principles.
  • Ability to lead and mentor teams in analytical modeling, model validation, and continuous model improvement.

Other signals

  • Develop, test, and deploy advanced data science solutions
  • Design, build, and validate predictive models leveraging machine learning and statistical techniques
  • Monitor model performance and implement lifecycle management