Senior Data Scientist - Search Ranking & NLP (GenAI)

Target; Sunnyvale (CA); Hybrid; USD 98,000 - 211,000; Full time

Job summary

Target is seeking a Sr Applied Data Scientist in Search to develop scalable ML models for ranking, personalization, and semantic retrieval across our Digital storefront. You will design offline and online experiments and build robust ML pipelines that scale to large retail catalogs.

You will apply embeddings, transformers, and vector search techniques while collaborating with Product, Engineering, and Infrastructure to drive business impact and maintain performance under strict latency

Qualifications

• 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
• Exceptional experience and understanding with retrieval/ranking systems, semantic search, NLP, vector search, or related ML domains
• Strong demonstrated coding skills in Python and SQL with experience in distributed data processing ecosystems
• Demonstrated experience building and deploying end to end production ML systems
• Strong understanding of production ML system tradeoffs including latency, scalability, reliability, and operational excellence
• Experience with modern ML approaches such as embeddings, transformers, semantic retrieval, RAG systems, or GenAI technologies
• Experience designing experiments and interpreting online/offline metrics
• Strong problem-solving skills with the ability to independently drive projects in moderately ambiguous environments
• Very good communication and cross-functional collaboration skills
• Constant learner mentality who stays current with new and evolving AI technologies via formal training and self-directed education

Responsibilities

• 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
• Partner closely with Product, Engineering, and Infrastructure teams to align technical solutions with business priorities and operational requirements
• Drive data-informed decision making through deep analysis, experimentation, and business impact measurement
• Balance model quality with latency, scalability, reliability, and infrastructure efficiency in large-scale production systems
• Contribute to best practices in experimentation, ML engineering, and operational excellence
• Mentor junior scientists and collaborate across teams to improve Search and Browse experiences

Skills

Search ranking

Semantic search

NLP

Vector search

GenAI/RAG

Experiment design

Production ML systems

Cross-functional collaboration

Education

PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics or related quantitative discipline

Tools

Python

SQL

Spark

Job description

Target is seeking a Sr Applied Data Scientist in Search to develop scalable ML models for ranking, personalization, and semantic retrieval across our Digital storefront. You will design offline and online experiments and build robust ML pipelines that scale to large retail catalogs.

You will apply embeddings, transformers, and vector search techniques while collaborating with Product, Engineering, and Infrastructure to drive business impact and maintain performance under strict latency