Staff Data Scientist- MLE - Recommendations & Personalization

What you'll do

We are seeking a Staff engineer to architect and lead the feature engineering ecosystem for large-scale recommendation and personalization systems. This role owns feature strategy, platform design, and cross-team alignment, while remaining hands-on for high-impact systems.

Responsibilities

Feature Platform & Architecture

• Design the end-to-end feature architecture supporting candidate generation, ranking, and re-ranking
• Lead the design and evolution of feature stores (offline + online) optimized for recsys workloads
• Define standards for feature versioning, lineage, freshness SLAs, and point-in-time correctness
• Architect systems supporting real-time, near-real-time, and batch features

Technical Leadership & Influence

• Drive feature engineering best practices across multiple recommendation teams
• Partner with Product and ML leadership to align feature strategy with personalization goals
• Mentor Senior engineers on recsys feature design and scalable data systems
• Review and approve designs for complex, high-risk feature pipelines

Advanced Recsys Enablement

• Enable cross-surface feature reuse (home feed, search, cart, last call, etc.)
• Lead efforts around feature observability, drift detection, and model health
• Anticipate future needs such as contextual personalization, cold-start handling, and diversity controls

Ownership & Execution

• Own critical feature pipelines that directly impact revenue and engagement
• Lead incident response for feature or data failures affecting ranking quality
• Balance long-term platform investments with short-term business priorities
• Explainability

Qualifications

• 4+ years in data engineering, ML engineering, or recsys platform roles
• Deep expertise in distributed systems and large-scale data processing
• Proven experience architecting feature platforms for recommendation systems
• Strong understanding of ranking architectures, candidate generation, and personalization patterns
• Exceptional technical communication and leadership skills

Benefits

Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much more.

Minimum Qualifications

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field

Preferred Qualifications

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.

The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.

Primary Location

1395 Crossman Ave, Sunnyvale, CA 94089-1114, United States of America