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

Job Id: R0000438138

This job is also available for the following locations

• 7000 Target Pkwy N, Brooklyn Park, MN

The pay range is $168,000.00 - $356,000.00

Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. 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.

JOIN TARGET AS A PRINCIPAL DATA SCIENTIST – SEARCH AND BROWSE

About Us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

A role with Applied Data Sciences team at Target means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Search, RecSys, Supply Chain Optimization or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Every Scientist on Target’s Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, and to elevate Target’s culture and apply retail domain knowledge.

About our Search and Browse team:

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. We are 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 we are building the architecture to lead it. We are solving some of the hardest problems in retail AI at a $10B+ commercial scale and 10K+ QPS, including:

• Architecting search and data systems for external LLM ingestion so our 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

We are looking for pragmatic builders and technical leaders who thrive on shipping production systems at scale. Engineering excellence, sub-second latency, operational reliability, infrastructure economics, and seamless integration with core Retrieval and Ranking systems matter just as much as modeling sophistication.

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

As a Principal Data Scientist – Search and Browse you’ll:

• 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

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

About you:

• 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

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ in Sunnyvale, CA or MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.

Target will consider for employment qualified applicants with criminal histories in a manner consistent with the San Francisco and City of Los Angeles Fair Chance Ordinances.

Benefits Eligibility

Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_F

Americans with Disabilities Act (ADA)

In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.  

Application deadline is : 06/18/2026