Sr Applied Data Scientist - Search and Browse (applied ML, LLMs, ML Ops)
About The Position
The Sr Applied Data Scientist will work on Target’s Search and Browse Applied Data Science team, which develops core relevance, retrieval, ranking, and personalization systems for Target’s digital experience across mobile and web. The team builds scalable machine learning systems to improve product discovery, semantic search, browse relevance, and customer engagement across large, dynamic retail catalogs. The role develops and deploys production machine learning models and systems for search ranking, browse personalization, semantic retrieval, and query understanding. It uses modern approaches such as embeddings, retrieval and ranking models, transformers, NLP, vector search, and GenAI/RAG, while balancing model quality with latency, scalability, reliability, and infrastructure efficiency. The position also contributes to experiments, feature pipelines, evaluation frameworks, production ML workflows, operational excellence, and cross-functional decisions. The work arrangement is Hybrid/Flex for Your Day, with work performed onsite at the assigned Target HQ location in Sunnyvale, California or Minnesota and virtually as role, team, and tasks require. Work duties cannot be performed outside the country of the primary work location unless otherwise prescribed by Target.
Requirements
- PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics, or a related quantitative discipline.
- 3+ years of industry experience in Machine Learning, Data Science, Search, NLP, Personalization, or related ML systems.
- Exceptional experience and understanding of retrieval/ranking systems, semantic search, NLP, vector search, or related ML domains.
- Strong 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 and offline metrics.
- Strong problem-solving skills and ability to independently drive projects in moderately ambiguous environments.
- Very good communication and cross-functional collaboration skills.
- A constant learner mentality, staying current with evolving AI technologies through formal training and self-directed education.
Responsibilities
- Develop and deploy scalable machine learning 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 machine learning workflows for production systems.
- Apply modern machine learning 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 with Product, Engineering, and Infrastructure teams to align technical solutions with business priorities and operational requirements.
- Drive data-informed decision-making through 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, machine learning engineering, and operational excellence.
- Mentor junior scientists and collaborate across teams to improve Search and Browse experiences.
Benefits
- Eligible team members and their dependents may receive comprehensive health benefits and programs, which may include medical, vision, dental, and life insurance.
- 401(k)
- Employee discount
- Short-term disability
- Long-term disability
- Paid sick leave
- Paid national holidays
- Paid vacation
- Financial, education, and well-being benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
