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

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