Description
We are seeking a Senior Applied Data Scientist to join our Search and Browse team at Target. As a Senior Applied Data Scientist, you will develop and deploy scalable ML models for search ranking, browse personalization, semantic retrieval, and query understanding systems.
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
Requirements:
- 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
Benefits:
- Comprehensive health benefits and programs
- 401(k)
- Employee discount
- Short term disability
- Long term disability
- Paid sick leave
- Paid national holidays
- Paid vacation