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

Target • Brooklyn Park, MN

13d • $168,000 - $356,000 • Hybrid

About The Position

The Principal Applied Data Scientist will define technical vision and organizational strategy for Target’s Search, Browse, and AI-driven discovery systems. The Search and Browse Applied Data Science team builds foundational relevance, retrieval, ranking, and personalized search systems for Target’s digital experience and is developing AI-native commerce discovery across search, browse, and conversational shopping.

The role leads architecture and innovation for large-scale retrieval, ranking, semantic search, and generative AI systems. Key challenges include enabling catalog ingestion by external LLMs and agentic commerce platforms, building zero-shot and cold-start discovery for seasonal inventory, addressing natural-language and long-tail queries over unstructured product catalogs, and evolving multi-stage retrieval and ranking systems. Solutions must balance relevance, latency, scalability, reliability, customer experience, business impact, and infrastructure cost.

The Principal Data Scientist leads ambiguous, multi-quarter initiatives across Product, Engineering, Applied Science, Infrastructure, and executive stakeholders; establishes scalable ML architecture, experimentation, and operational practices; and mentors scientists and technical leaders. The position is described as Hybrid/Flex for Your Day, with a potential Remote or Hybrid arrangement based on Target’s needs. Work must be performed in the country of the primary work location unless otherwise prescribed by Target.

Requirements

• PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics, or a 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.

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.
• Drive innovation across transformers, LLMs, RAG architectures, multi-stage ranking, personalization, conversational commerce, and agentic AI.
• Architect search and retrieval systems for integration with external LLM and agentic search ecosystems.
• Define the future evolution of semantic retrieval, conversational search, and zero-shot discovery systems.
• Influence organization-wide strategy for relevance, experimentation, evaluation, ML infrastructure, and AI product investments.
• Lead 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 align stakeholders on major technical and product decisions.
• Influence technical direction and investment priorities across multiple teams and organizations.

Benefits

• Eligible team members and their dependents may receive comprehensive health benefits and programs, which may include medical, vision, dental, and life insurance.
• 401(k).
• Employee discount.
• Short-term disability.
• Long-term disability.
• Paid sick leave.
• Paid national holidays.
• Paid vacation.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal