Description
The pay range for this role is $168,000.00 - $356,000.00, based on several factors including labor markets, education, work experience, and certifications.
As a Principal Data Scientist – Search and Browse at Target, you will be part of the Applied Data Sciences team, developing and managing state-of-the-art predictive algorithms that use data at scale to automate and optimize decisions.
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. You will be working on architecting search and data systems for external LLM ingestion, building zero-shot and cold-start discovery systems, solving natural language and long-tail search problems, and evolving multi-stage retrieval and ranking architectures.
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
- Influence technical direction and investment priorities across multiple teams and organizations
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:
- Comprehensive health benefits and programs
- 401(k)
- Employee discount
- Short term disability
- Long term disability
- Paid sick leave
- Paid national holidays
- Paid vacation