Senior Applied Data Scientist, Search and Browse

Target

Hybrid

Quick summary

Work type: Hybrid
Location: Sunnyvale, CABrooklyn Park, MN
Salary: $98,000–$211,000 / yr
Posted: 5 days ago
Closes: Jul 31, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $168k

This role $154k

$83k most similar roles pay here $240k

This role pays less than 66% of similar roles. Most pay $126,800–$209,750 — the shaded band above. At the midpoint, this role pays about $154k 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 · Senior Applied Data Scientist, Search and Browse

Role Posting Log in to save

As a Senior Data Scientist on Target’s Search and Browse team, you will develop and deploy scalable machine learning models for search ranking, browse personalization, semantic retrieval, and query understanding systems. You’ll design experiments to enhance relevance, engagement, and customer satisfaction while building feature pipelines and evaluation frameworks for production systems. This role requires expertise in modern ML techniques like embeddings, transformers, NLP, vector search, and GenAI/RAG systems, along with strong coding skills in Python and SQL within distributed data processing ecosystems. You will collaborate closely with Product, Engineering, and Infrastructure teams to ensure technical solutions align with business priorities while balancing model quality with latency, scalability, and reliability constraints. Ideal candidates hold a PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics, or related fields, with 3+ years of industry experience in ML systems, retrieval/ranking, semantic search, and NLP domains.

Skills

Python SQL Kubernetes Terraform Docker CI/CD Prometheus Grafana PostgreSQL AWS NLP GenAI RAG LLMs Vector_search Embeddings Transformers Semantic_retrieval Search_ranking Browse_personalization

What you'll do

Develop and deploy scalable ML models for search ranking, browse personalization, semantic retrieval, and query understanding systems.
Design and execute offline and online experiments to improve relevance, engagement, conversion, and customer satisfaction.
Build scalable feature pipelines, evaluation frameworks, and ML workflows for production systems.
Apply modern ML techniques including embeddings, retrieval/ranking models, transformers, NLP, vector search, and GenAI/RAG systems.
Improve query understanding, catalog understanding, semantic retrieval, and long-tail search relevance across large retail catalogs.

What we're looking for

PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics, or related quantitative discipline.
3+ years of industry experience in Machine Learning, Data Science, Search, NLP, Personalization, or related ML systems.
Strong coding skills in Python and SQL with experience in distributed data processing ecosystems.
Demonstrated hands-on experience building and deploying production ML systems at scale.
Exceptional experience with retrieval/ranking systems, semantic search, NLP, vector search, or related ML domains.
Experience with modern ML approaches such as embeddings, transformers, semantic retrieval, RAG systems, or GenAI technologies.

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