Lead Data Scientist- Comp Intel

A role with Target Data Science Engineering means the chance to help develop state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, you'll be challenged to harness Target s impressive data breadth to build the algorithms that power solutions our partners in Merchandizing, Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Team Overview Target- Data Science Competitive Intelligence team is offering an exciting opportunity to solve state-of-the-art problems for Competitor Product matching. The team is rapidly growing and creating massive business impact by building cutting edge systems. We use NLP, deep learning, classical machine learning, transformer based architectures, and GenAI/Agentic AI (including RAG pipelines, LLM-powered agents, and tool-use frameworks) to build best in-class data products. As we build the future of Competitive Intelligence, we are looking for driven and passionate individuals with deep expertise in developing AI/ML systems at scale and leading high impact charters. If you are that person, you can expect to be involved in: Leading the design, development, productionization and ongoing upkeep of AIML systems across Competitive Product Classification, Matching and Validation. Owning technical direction for a problem area: defining strategy, influencing roadmaps, setting quality bars, and driving execution through a team of scientists and engineers Architecting end-to-end solutions that integrate AIML modeling, experimentation (offline + online), and engineering systems for scalability, latency, and reliability, including transformer based models, embedding systems, and retrieval-augmented generation (RAG) pipelines. Developing a multiyear vision for key ML AI capabilities Competitive Intelligence, aligned to business outcomes and measurable metrics Serving as a technical leader and mentor, raising the bar for scientific rigor, design reviews, and best practices across the org anization Preferred Domain Experience We re looking for strong domain depth and evidence of impact in NLP / Deep Learning / Agentic AI GenAI / Search Information retrieval (e-commerce or large-scale Retail or consumer products preferred), including Transformers, semantic search, vector databases, RAG systems, and autonomous/agent-based workflows About You 4-year degree in a quantitative discipline (Science, Technology, Engineering, Mathematics) or equivalent practical experience 7+ years of professional data science / applied ML experience (or equivalent), with a strong track record of delivering production AIML systems and measurable business impact Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.