Principal Data Scientist: ML Innovation Lead (Onsite, Bellevue)

Walmart Global Tech; Bellevue (WA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

401(k) match

Stock purchase plan

Paid parental leave

PTO

Health plans

Job summary

Walmart Global Tech is seeking a Principal Data Scientist to lead the development and deployment of advanced ML models that address complex business challenges for the global ecommerce platform. You will mentor teams, collaborate across functions, and deliver high-quality data products with measurable business impact.

The role requires deep expertise in ML, deep learning, and GEN AI techniques, plus hands-on experience with production-grade pipelines on AWS SageMaker.

Qualifications

• PhD in Computer Science or related field is strongly preferred.
• Proven ability to architect and deploy large-scale ML systems.
• Experience with end-to-end data science lifecycle and productionization.

Responsibilities

• Develop, test, and deploy advanced ML models aligned with business goals.
• Analyze complex problems to identify root causes and tech-driven solutions.
• Identify and validate data sources for analytical modeling.
• Lead feature engineering, EDA, and model evaluation to improve performance.
• Collaborate with product and business stakeholders to scale data science products after prototyping.
• Mentor team members on modeling, visualization, and best practices.
• Drive continuous improvement by adopting emerging ML trends and automation.
• Translate business needs into scalable data science strategies with measurable outcomes.

Skills

Python

AWS SageMaker

Leadership

Communication

ML algorithms

Education

PhD in Computer Science or related field

Master’s degree in related field

Tools

AWS SageMaker

Job description

Walmart Global Tech is seeking a Principal Data Scientist to lead the development and deployment of advanced ML models that address complex business challenges for the global ecommerce platform. You will mentor teams, collaborate across functions, and deliver high-quality data products with measurable business impact.

The role requires deep expertise in ML, deep learning, and GEN AI techniques, plus hands-on experience with production-grade pipelines on AWS SageMaker.