This role pays more than
88%
of similar roles. Most pay
$153,178–$242,500
— the shaded band above.
At the midpoint, this role pays about
$262k
versus about
$198k
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
60 open roles
on FindRole.
Listed pay typically runs
$98,000–$176,000
across 50 roles with salary data.
Principal Applied Data Scientist - Search and Browse (NLP, Vector Search, LLMs) joins the Applied Data Sciences team to build foundational relevance, retrieval, ranking, and personalized search systems for a digital commerce experience. This role involves defining long-term technical visions and roadmaps for AI-driven discovery, including architecture strategies for large-scale retrieval, semantic search, and GenAI systems. The candidate will develop multi-stage ranking architectures, RAG systems, and zero-shot discovery tools to solve complex problems like conversational queries against massive unstructured product catalogs. Key technologies include Python, VertexAI, transformers, LLMs, and vector search. The role addresses the challenge of integrating external LLM ingestion for agentic commerce while balancing sub-second latency, scalability, and infrastructure efficiency. This position requires expertise in NLP, recommendation systems, and ML infrastructure to drive innovation across search and browse platforms at a massive commercial scale.
Machine Learning
Deep Learning
PyTorch
JAX
Python
SQL
Spark
Generative AI
Search
Ranking
Retrieval
Optimization
Statistics
Probability Theory
Linear Algebra
Agile
Experimental Design
Data Processing
Machine Learning
Python
Go
Large Language Models (LLMs)
Natural Language Processing (NLP)
Information Retrieval
Retrieval-Augmented Generation (RAG)
Prompt Engineering
Data Science
A/B Testing
Statistical Hypothesis Testing
Data Pipelines
Distributed Inference
Model Quantization
Search Ranking
Generative AI
Python
LangChain
AWS
Vector Databases
RAG
Machine Learning
Deep Learning
NLP
SQL
Scala
R
Statistics
Time Series
Clustering
Classification
Sentiment Analysis
Data Science