Sr Applied Data Scientist - Search and Browse (applied ML, LLMs, ML Ops)

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 .

The Search and Browse Applied Data Science team builds the core relevance, retrieval, ranking, and personalization systems that power Target’s Digital experience. We develop scalable ML systems that improve product discovery, semantic search, browse relevance, and customer engagement across Mobile and Web platforms.

E-commerce Search is rapidly evolving with advances in LLMs, semantic retrieval, and conversational AI. We are building next-generation discovery experiences that help millions of guests find the right products quickly and intuitively across massive and constantly changing retail catalogs.

Our team is solving large-scale Search challenges at enterprise scale, including natural language and long-tail search, semantic retrieval, zero-shot item understanding, and AI-native commerce discovery experiences operating at 10K+ QPS with strict latency and reliability requirements.

• 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

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

• 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

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, CA or MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click  if you are curious to learn more about Minnesota.