(usa) Principal, Data Scientist

Walmart · Retail · Hoboken, NJ +1

Principal Data Scientist at Walmart focused on developing and deploying advanced analytical models using Double Machine Learning and Causal Modeling. The role involves generating data-driven insights, collaborating across functions, mentoring team members, and ensuring the quality and impact of data insights. The team focuses on scalable, data-driven solutions for Ad-tech, including autonomous AI agents and reliable applications.

What you'd actually do

  1. Develop, test, and deploy advanced data science solutions using programming languages such as Python and SQL to address complex business challenges.
  2. Analyze business problems to identify root causes and recommend data-driven approaches aligned with strategic objectives.
  3. Identify, source, and validate high-quality data from multiple systems to support analytical modeling and insights generation.
  4. Lead the design and implementation of machine learning models, including feature engineering, model tuning, and validation to ensure accuracy and robustness.
  5. Collaborate with stakeholders to translate business requirements into actionable data strategies and visualization frameworks.

Skills

Required

  • Python
  • SQL
  • Java
  • feature engineering
  • predictive scoring model development
  • causal modeling
  • forecasting
  • scenario modeling
  • leadership skills

Nice to have

  • machine learning algorithms
  • deep learning
  • statistical analysis
  • optimization models
  • PhD in Machine Learning
  • Computer Science
  • Information Technology
  • Operations Research
  • Statistics
  • Applied Mathematics
  • Econometrics
  • Publications
  • active peer review

What the JD emphasized

  • advanced analytical models
  • Double Machine Learning
  • Causal Modeling
  • machine learning models
  • feature engineering
  • model tuning
  • model lifecycle management

Other signals

  • deploy advanced analytical models
  • generate robust, data-driven insights
  • lead the design and implementation of machine learning models
  • deploy scalable models and maintaining model lifecycle management in production environments