Lead Data Scientist - Advanced AI (Applied ML, Agentic, Gen AI)

Target • Brooklyn Park, NC

7h • Hybrid

About The Position

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.

Requirements

• PhD or 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.)
• Strong understanding of the model development lifecycle, including problem framing, data exploration, feature engineering, model selection, experimentation, validation, evaluation, deployment partnership, monitoring, and continuous improvement
• Ability to define clear success metrics and evaluation strategies for AI/ML systems, including both offline and production-facing measures of quality, reliability, adoption, and business impact
• Experience deploying models, prototypes, or AI/ML capabilities into production applications
• Ability to translate ambiguous business problems into structured data science and modeling approaches
• Strong communication skills, with the ability to explain complex AI/ML concepts, tradeoffs, risks, and recommendations to technical partners, business stakeholders, and leaders
• Experience working in large enterprise environments with data governance, privacy, security, platform, and operational requirements
• Self-driven and results-oriented, with strong ownership, sound judgment, curiosity, and the ability to move quickly while maintaining high technical standards
• Collaborative team player with a commitment to continuous learning, knowledge sharing, responsible AI practices, and building reliable AI/ML systems that create business value

Nice To Haves

• Experience working with LLMs, prompt engineering, retrieval-augmented generation, agentic workflows, model APIs, embeddings, evaluation frameworks, or AI observability tools is strongly preferred
• Ability to mentor applied data scientist, contribute to technical direction and raise the quality of data science practices within a team

Responsibilities

• Help identify, design, develop, evaluate, and scale AI/ML capabilities that drive automation, insight, and action across core business workflows.
• Provide hands-on data science leadership across Advanced AI initiatives.
• 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.
• Work across LLM-powered applications, classical machine learning, deep learning, retrieval-augmented generation, agentic systems, intelligent automation, and other applied AI patterns where appropriate.
• Partner with engineering teams to ensure AI/ML solutions are reliable, measurable, maintainable, and aligned to Target’s enterprise standards.
• Contribute to evaluation strategies, model monitoring approaches, feedback loops, human-in-the-loop workflows, and responsible AI practices.
• 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.
• 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.

Benefits

• Comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more
• 401(k)
• Employee discount
• Short term disability
• Long term disability
• Paid sick leave
• Paid national holidays
• Paid vacation

What This Job Offers

• Job Type: Full-time
• Career Level: Senior