Want to get hired at Walmart?

Senior Data Scientist

Walmart

Bellevue, Washington, United StatesOn Site

Original Job Summary

Senior Data Scientist

This notice is provided as a result of the filing of an Application for Permanent Alien Labor Certification. All interested parties may submit documentary evidence to the Certifying Officer at the U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification.

What you'll do

Position: Senior Data Scientist Location: 10500 NE 8th Street (13th floor), Bellevue, WA 98004

  • Provide recommendations to business stakeholders to solve complex issues.
  • Develop business cases with ROI or cost savings projections.
  • Translate business requirements into projects, activities, and tasks.
  • Apply machine learning and AI techniques including deep learning and auto ML.
  • Deploy models to production and continuously monitor performance.
  • Develop solutions using Python, SQL, and various data libraries.

Required Skills & Experience

  • Expertise in Python libraries (NumPy, Pandas, scikit-learn).
  • Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
  • Strong background in developing, training and deploying ML/DL models.
  • Proficient in ETL processes and efficient SQL query writing.
  • Knowledge in using frameworks like TensorFlow, Keras, and PyTorch.

Compensation & Benefits

Salary Range: $118,414/year to $216,000/year; additional performance incentives, stock equity, and comprehensive benefits including medical, vision, dental, 401(k), company discounts, and paid time off.

Key skills/competency

Senior Data Scientist, Python, ML, DL, cloud, SQL, ETL, analytics, Docker, Kubernetes

How to Get Hired at Walmart

🎯 Tips for Getting Hired

  • Research Walmart's culture: Understand their mission and recent retail innovations.
  • Customize your resume: Emphasize data science and ML experiences with specifics.
  • Highlight cloud expertise: Showcase AWS, Azure or GCP project work.
  • Practice technical interviews: Focus on coding, model building and debugging.

📝 Interview Preparation Advice

Technical Preparation

Review Python libraries and machine learning frameworks.
Practice coding challenges and model deployment exercises.
Study cloud platform basics and container orchestration.
Prepare test cases and code optimization techniques.

Behavioral Questions

Describe managing complex projects under pressure.
Explain teamwork in challenging technical setups.
Share conflict resolution experiences in data projects.
Discuss adaptation to evolving business needs.