Principal Data Scientist
@ Walmart

Sunnyvale, California, United States
On Site
Full Time
Posted 4 days ago

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Job Details

About the Role

The Principal Data Scientist at Walmart will develop robust data solutions and drive business value by leveraging advanced analytics and machine learning techniques.

Key Responsibilities

  • Write code to develop applications using various programming languages.
  • Create test cases, proofs of concept, and deploy software to production.
  • Analyze business problems, quantify impact, and recommend technology solutions.
  • Translate business requirements into strategies and measurable deliverables.
  • Design data visualizations, develop models, and guide feature engineering.
  • Deploy, monitor, and maintain models while ensuring robust testing and documentation.

Required Skills & Technologies

  • Real time event processing and distributed systems development.
  • Software development in Java, J2EE, JavaScript, and Python.
  • Enterprise Application Integrations including Kafka, TIBCO.
  • Experience with SQL, NoSQL, OLAP databases, and RESTful APIs.
  • Cloud technologies: AWS, GCP, Azure and real-time data systems.
  • Expertise in machine learning, artificial intelligence, and model tuning.

Location & Compensation

This role is based at 1375 Crossman Avenue, Sunnyvale, CA 94089. The salary range is $210,709/year to $286,000/year with additional performance incentives, equity incentives, and benefits.

Key Skills/Competency

  • Data Science
  • Machine Learning
  • Analytics
  • Java
  • Python
  • Cloud
  • Kafka
  • SQL
  • Visualization
  • RESTful
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How to Get Hired at Walmart

🎯 Tips for Getting Hired

  • Research Walmart's culture: Understand company values, mission, and recent news.
  • Customize your resume: Highlight analytics and machine learning projects.
  • Showcase technical skills: Detail experience with Java, Python, and cloud.
  • Prepare for interviews: Emphasize problem-solving and real-time data processing.

📝 Interview Preparation Advice

Technical Preparation

Review coding in Java and Python.
Practice model deployment and API integrations.
Study cloud services and distributed systems.
Refresh SQL/NoSQL and data processing techniques.

Behavioral Questions

Describe handling complex data challenges.
Explain collaboration with cross-functional teams.
Discuss decision-making under project pressure.
Illustrate problem-solving in uncertain scenarios.

Frequently Asked Questions