Lead Data Scientist - Advanced AI (Applied ML, Agentic, Gen AI)
Target
- Location
- 7000 Target Pkwy N,NCD-0375 Brooklyn Park,MN 55445
- Work model
- On-Site
- Level
- Senior
- Salary
- $132k – $238k/yr
- Posted
- 19h ago
Skills
About this role
The pay range is $132,000.00 - $238,000.00 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 https://corporate.target.com/careers/benefits . JOIN TARGET AS A LEAD DATA SCIENTIST – ADVANCE AI / AI FACTORY About us: Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here .
About the role
Target’s Advanced AI team builds end-to-end AI/ML systems that create meaningful business value across the enterprise. These systems may be powered by LLMs, classical machine learning, or deep learning models, and are designed as scalable, reliable, production-grade applications, including agentic architectures where they add clear value. As a Lead Data Scientist for Advanced AI, you will help identify, design, develop, evaluate, and scale AI/ML capabilities that drive automation, insight, and action across core business workflows. You will work closely with AI Engineers, Full-Stack Engineers, product partners, platform teams, security teams, and business stakeholders to translate ambiguous business problems into practical AI/ML solutions. In this role, you will provide hands-on data science leadership across Advanced AI initiatives. You will frame problems, define success metrics, explore data, develop modeling approaches, design experiments, evaluate model and system performance, and help guide solutions from prototype to production. You will work across LLM-powered applications, classical machine learning, deep learning, retrieval-augmented generation, agentic systems, intelligent automation, and other applied AI patterns where appropriate. You will also partner with engineering teams to ensure AI/ML solutions are reliable, measurable, maintainable, and aligned to Target’s enterprise standards. This includes contributing to evaluation strategies, model monitoring approaches, feedback loops, human-in-the-loop workflows, and responsible AI practices. You will help shape technical approaches, identify risks, resolve ambiguity, mentor other Data Scientists, and support the evolution of reusable AI/ML patterns for the broader Advanced AI team. A successful Lead Data Scientist will help deliver production-grade AI/ML applications that create measurable business value while raising the quality of data science, experimentation, evaluation and applied AI practices across the team. Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
About you
PhD or MS in MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Physics or a related technical field preferred 7+ years of hands-on experience in data science, machine learning, applied AI, or AI/ML systems Demonstrated experience developing and evaluating AI/ML solutions including solutions powered by LLMs, classical machine learning models and deep learning models Strong proficiency with Python programming in common data science, machine learning and deep learning libraries (Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, etc.) Experience working with LLMs, prompt engineering, retrieval-augmented generation, agentic