Principal Applied Data Scientist, Search and Browse

Target

Hybrid

Quick summary

Work type: Hybrid
Location: Sunnyvale, CABrooklyn Park, MN
Salary: $168,000–$356,000 / yr
Posted: 5 days ago
Closes: Jul 24, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $168k

This role $262k

$94k most similar roles pay here $384k

This role pays more than 95% of similar roles. Most pay $126,800–$209,750 — the shaded band above. At the midpoint, this role pays about $262k versus about $168k for comparable roles.

Based on 240 similar postings.

Employer

About Target

Target Corporation is a large-format general merchandise and grocery retailer offering a wide assortment of everyday essentials, apparel, home goods, and electronics through stores and online. Industry: General Merchandise Retail

Target currently has 51 open roles on FindRole.

Listed pay typically runs $118,000–$211,000 across 51 roles with salary data.

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View all roles at Target

At a glance

TL;DR · Principal Applied Data Scientist, Search and Browse

Role Posting Log in to save

As a Principal Data Scientist on Target’s Search and Browse team, you will lead the development of advanced AI-driven commerce discovery systems at scale. You’ll define long-term technical visions and organizational roadmaps for search, browse, and conversational shopping experiences, architecting large-scale retrieval and ranking systems that integrate external LLMs. Your responsibilities include driving innovation in semantic search, personalization, and multi-stage ranking architectures while ensuring sub-second latency and operational reliability. With deep expertise in NLP, vector search, and ML infrastructure, you will mentor technical leaders, influence executive stakeholders, and establish best practices across multiple teams. This role requires a PhD or MS in Computer Science, Statistics, or related fields, along with 8+ years of experience building scalable ML systems for Search, Recommendation, Personalization, Ads, or AI platforms.

Skills

Python VertexAI LLMs RAG NLP Semantic Retrieval Vector Search Conversational Search Multi-Stage Ranking Personalization Recommendation Systems Infrastructure Cost Management CI/CD Kubernetes Docker Prometheus Grafana

What you'll do

Define long-term technical vision and roadmap for search, browse, and AI-driven discovery systems.
Lead architecture strategy for large-scale retrieval, ranking, semantic search, and GenAI systems.
Drive innovation in transformers, LLMs, RAG architectures, multi-stage ranking systems, personalization, conversational commerce, and agentic AI.
Architect search and retrieval systems for integration with external LLM and agentic search ecosystems.
Establish scalable ML architecture patterns, experimentation standards, and operational best practices across teams.
Mentor lead scientists and technical leaders while influencing organizational strategy on major technical decisions.

What we're looking for

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, and agentic AI systems
Deep expertise in retrieval/ranking architectures, recommendation systems, NLP/LLMs, experimentation, and ML infrastructure (VertexAI)
Proven ability to define 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 track record driving measurable business impact through ML innovation

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