(usa) Principal, Data Scientist

Walmart Walmart · Retail · Crossman Respect Building CA SUNNYVALE, J STREET SPACE AR BENTONVILLE

Principal Data Scientist to lead the development and deployment of advanced analytical models and machine learning solutions for Last Mile Delivery at Walmart, focusing on optimizing routing, pricing, driver matching, delivery commitments, and capacity management. The role involves applying advanced data strategies and ML techniques to ensure platform trust and safety, collaborating with stakeholders, and developing innovative solutions to enhance operational efficiency and customer satisfaction.

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, assess, and validate data sources ensuring quality and relevance for modeling and analytics.
  4. Design, build, and validate predictive and prescriptive models leveraging machine learning, deep learning, and statistical techniques.
  5. Collaborate with stakeholders to translate business requirements into actionable data strategies and measurable outcomes.

Skills

Required

  • Python
  • SQL
  • Statistical analysis
  • Machine learning
  • Deep learning
  • Model development
  • Data strategy
  • Data visualization

Nice to have

  • Reinforcement learning
  • Solution architecture
  • Data sourcing
  • Data quality assessment
  • Data ecosystem management
  • Model validation
  • Model tuning
  • Model deployment
  • Lifecycle management
  • Mentoring
  • PhD in Machine Learning
  • Computer Science
  • Information Technology
  • Operations Research
  • Statistics
  • Applied Mathematics
  • Econometrics
  • Publications

What the JD emphasized

  • Extensive experience in developing and deploying machine learning and deep learning models
  • Proficiency in statistical analysis, exploratory data analysis, and advanced modeling techniques including reinforcement learning and solution architecture.
  • Expertise in model validation, tuning, deployment, and lifecycle management

Other signals

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