Principal Applied Data Scientist - Search and Browse (NLP, Vector Search, LLMs)

Quick Facts

Pay range: $168,000.00 - $356,000.00

Description

Principal Data Scientist – Search and Browse

The Search and Browse Applied Data Science team builds the foundational relevance, retrieval, ranking, and personalized search systems that power Target’s Digital experience at scale, defining the future of AI-native commerce discovery across Search, Browse, and emerging conversational shopping experiences.

E-commerce Search is undergoing a massive transformation, and the team is building the architecture to lead it, solving hard problems in Retail AI at a $10B+ commercial scale and 10K+ QPS, including:

• Architecting search and data systems for external LLM ingestion so the catalog wins in ChatGPT, Gemini, agentic commerce, and the next generation of AI-native discovery experiences
• Building zero-shot and cold-start discovery systems for rapidly changing, seasonal retail inventory
• Solving natural language and long-tail search problems where conversational queries and traditional retrieval systems break against massive unstructured product catalogs
• Evolving multi-stage retrieval and ranking architectures that balance relevance quality, latency, scalability, and infrastructure efficiency at enterprise scale

This role requires deep technical expertise, exceptional product judgment, and the ability to influence organizational strategy while driving measurable customer and business impact.

Responsibilities

• Define the long-term technical vision and organizational roadmap for Search, Browse, and AI-driven discovery systems
• Lead architecture strategy for large-scale retrieval, ranking, semantic search, and GenAI systems operating at massive scale
• Drive innovation across transformers, LLMs, RAG architectures, multi-stage ranking systems, personalization, conversational commerce, and agentic AI
• Architect search and retrieval systems for external LLM and agentic search ecosystem integration
• Define the future evolution of semantic retrieval, conversational search, and zero-shot discovery systems
• Influence organization-wide strategy across relevance, experimentation, evaluation, ML infrastructure, and AI product investments
• Lead highly ambiguous, multi-quarter initiatives involving Product, Engineering, Applied Science, Infrastructure, and executive stakeholders
• Establish scalable ML architecture patterns, experimentation standards, and operational best practices across multiple teams
• Drive foundational investments and technical direction across Search, Retrieval Infrastructure, and AI-powered discovery platforms
• Balance customer experience, business impact, system reliability, latency, scalability, and infrastructure cost at enterprise scale
• Mentor Lead scientists and technical leaders across the organization
• Represent the organization in executive reviews and drive alignment on major technical and product decisions

Requirements

• PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics or related quantitative discipline
• 8+ years of industry experience building and scaling ML systems for Search, Recommendation, Personalization, Ads, or AI platforms
• Strong experience with semantic retrieval, vector search, RAG systems, conversational search or agentic AI systems
• Deep expertise in retrieval/ranking architectures, recommendation systems, semantic search, NLP/LLMs, experimentation and ML infrastructure (VertexAI)
• Demonstrated Python programming and technical ML problem-solving skills
• Proven experience defining architecture and long-term strategy for large-scale production AI systems
• Experience operating large-scale online systems with strict latency, scalability, reliability, and infrastructure cost requirements
• Strong understanding of retrieval/ranking system tradeoffs, experimentation strategy, and operational excellence
• Strong track record driving measurable business impact through ML innovation
• Experience leading cross-functional initiatives spanning multiple teams or organizations
• Ability to influence executive stakeholders and drive organizational technical direction
• Exceptional communication, technical leadership, strategic thinking, and mentoring skills

Benefits

Pay is based on several factors which vary based on position, including labor markets and in some instances may include education, work experience and certifications.

Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more.

Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation.

Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.

Hybrid/Flex for Your Day

This position operates as a Hybrid/Flex for Your Day work arrangement based on Target’s needs, requiring core work both onsite at Target HQ in Sunnyvale, CA or MN location and virtually, depending on role, team, and tasks. Work duties cannot be performed outside of the country of the primary work location.